In collaboration with the PLDI organizing commitee, the CCC is happy to announce the winners of the FIT session:

1) Outfoxing the Mammoths, by Marek Olszewski and Saman Amarasinghe, Massachusetts Institute of Technology;

2) Resource-Based Programming in Plaid, by Jonathan Aldrich, Carnegie Mellon University; and

3) Dualities in Programming Languages, by Martin Hirzel and Priya Nagpurkar.

These three were selected based on an online poll of registered participants of PLDI. Olszewski, Aldrich, and Hirzel will each receive travel grants. Their presentations and papers can be found on the FIT Web page.

Many thanks to the PLDI community! And please check out the presentations and comment about them below.

(Contributed by Frans Kaashoek, Massachusetts Institute of Technology)

Specifically, Gabriel started by highlighting five key changes that have occurred at DARPA in the past year:

- “Go/no-go” is gone.

- Contracting has been simplified. The process is as clear, simple, and fast as the law allows.

- More realistic conflict of interest rules have been applied to people coming to work at DARPA.

- Program managers are once again managing programs.

- Program managers have been reeducated about the need to consider basic research as a critical element of their programs.

He further reeled off three directions moving forward:

- Manufacturing. “One of the biggest challenges we face as a nation is a decline in our ability to make things,” he said. “Americans consume more goods today than ever before – and yet we are less likely to be employed in manufacturing than we have been at any time in the past 100 years. [But] to innovate, we must make. It’s hard to build and field systems needed to protect the nation with a service economy.” Gabriel stated that DARPA is identifying and building on the fundamental challenges in making things.

- Edge-finding. “We often talk of globalization as boundless,” he said. “But sociologists will tell you that as long as there are humans involved there are boundaries. In the cyberworld, our inability to define the edges is a world of peril. This is one of the most technically challenging tasks of our time.” Gabriel challenged us to understand the following: What are the edges of truth in this environment? How do we assess them? How are they relevant?

- Cyber. “In 2010 and 2011, DARPA will invest over $300M in cyber-enabled initiatives,” Gabriel advised. “DARPA-developed technologies are already prevalent in both government and commercial venues. For example, DARPA technology protects DARPA servers again denial-of-service attacks.” DARPA is pursuing several new initiatives, including clean-slate technology on adaptive posts for resilience; safer computing that seeks to create assured confrontations on un-trusted hardware without the traditional performance sacrifices; etc.

Finally, Gabriel called on the computing research community to help by getting to work:

So today, I’d like to call you to action. [It’s] a call to return to the core values of the agency. A call to service. And a call to collectively reach for something bigger – more expansive – and more enduring. This is the time to dig deep and go to the edge – to find the nerve together.

At DARPA, we say you can’t lose your nerve.

The deputy director’s talk underscores the dramatic evolution of DARPA that we have witnessed in just the past year.

(Contributed by Erwin Gianchandani, CCC Director)

The hearing began with a session on “Science, Technology, and Diplomacy” that featured the three founding members of the Science Envoys program – Bruce Alberts, Elias Zerhouni, and Ahmed Zewail – speaking candidly about their experiences as part of this new diplomatic effort, which places U.S. scientists in foreign nations to promote international relations. The three envoys shared insights they had gleaned while trying to improve diplomatic relations with Indonesia, Egypt, Algeria, Qatar, Turkey, and the U.A.E.

A prevailing sentiment was the urgent need for a “focus on capacity building.” Instead of taking technologies to foreign nations, we need to teach these nations to teach themselves, the envoys reported. Further, they commented that, while STEM education is lacking in the U.S., it is even worse in developing nations. The world currently has an estimated shortage of 10 million teachers, and the science education per capita continues to decrease each year.

Each envoy reported receiving surprisingly warm receptions as a science diplomat – and felt the program should be expanded. The envoys also argued that the role of the “State Department scientist” could not likely be salvaged from its current status as “career-ending.” Instead, they urged science agencies, such as the National Science Foundation, to adopt rotational programs to send experts to various foreign embassies for short periods of time.

All in all, the session presented hope that Science Envoys could be an effective tool in diplomacy in the future.

Later in the day, PCAST heard updates from two previously commissioned efforts:

- A panel on health information technology reported the completion of a draft report (to be made available to the public soon, following a final round of edits) that calls for strengthening the role of the Office of the National Coordinator for Health IT within the Dept. of Health & Human Services – primarily by advocating and promulgating standards for exchange and privacy of secure electronic health information – in an attempt to improve quality and safety of healthcare, while simultaneously reducing cost. Unfortunately, it appears the report will be fairly narrow in focus, specifically discussing only electronic medical records (EMRs) – and not HIT broadly.

- PCAST members evaluating STEM education described the hope of new technology in advancing education – including the creation of deeply digital materials (e.g., interactive simulations, videos, built-in tutors, etc.) that (a) are increasingly adaptive to what a student is learning, (b) assist in ongoing and cumulative assessments of students, and (c) provide professional development support to teachers; etc. The subcommittee co-chairs, Eric Lander and Jim Gates, signaled very clearly that these issues would be part of the final report – which may be ready by the September PCAST meeting. Lander and Gates again solicited feedback from the public about Ed Tech.

Please view an archived webcast of the hearing (see the PCAST website), and as always comments are greatly appreciated below.

(Contributed by Erwin Gianchandani, CCC Director, & Chase Hensel, CRA/CCC Tisdale Fellow)

In particular, the article highlights Paro — a robotic baby harp seal — used in nursing homes as a therapeutic aid for the elderly. Paro uses 14 different sensors, two microprocessors, and a whole slew of AI algorithms to illicit compassionate responses from users and convincingly behave as a real-life animal. The Paro robot is used to help patients suffering with dementia and provide comfort in times of distress.

Harmon goes on to talk about other synthetic companions, which use artificial intelligence to interact with people, inducing behavioral changes. She describes an AI device that can help with weight loss and another that can prevent relapses into addiction.

Interestingly, Harmon also delves into the philosophical concerns surrounding these types of artificial companions and posits that technology is currently moving faster than the philosophy around it.

Definitely check out the feature in the NY Times Magazine, as well as the media that accompany it:

- A video of a patient interacting with Paro; and

- A timeline detailing the history of robotics.

And be sure to post your thoughts below!

(Contributed by Chase Hensel, CRA/CCC Tisdale Fellow)

In the second in a fascinating series of articles titled “Smarter Than You Think” being published by The New York Times Magazine this summer, writers Steve Lohr and John Markoff illustrate how artificial intelligence is transforming how we answer questions, complete simple tasks, and assist one another.

This Sunday’s story highlights the work of Eric Horvitz, a member of the CCC Council, whose team at Microsoft Research has developed a “medical avatar” that can understand speech, recognize symptoms of pediatric conditions, and reason according to simple rules. The avatar is able to interface with real-life patients and make initial diagnoses of their ailments, much as any medical assistant would. All the while, it’s piquing the curiosity and earning the trust of the children it’s serving — a future generation of computer users.

Eric’s team is also working on a related class of “digital assistants”; visitors to his office are greeted by an avatar who knows all about his schedule and meeting habits. And as The Times‘ story emphasizes, these technologies and others like it are affecting many facets of our daily lives, from in-car GPS navigation systems to iPhone apps, from telemarketers to product manufacturers’ support centers, etc.

I encourage you to read this outstanding feature in Sunday’s New York Times Magazine — and to explore the terrific interactive multimedia accompanying it:

- The medical avatar in action;

- How the medical avatar could change future visits to the doctor; and

- A timeline detailing how far we’ve come in natural language processing, machine learning, data mining, etc.

And you can learn more about Eric’s work on his website: http://research.microsoft.com/en-us/um/people/horvitz/.

(Contributed by Erwin Gianchandani, Director, CCC)

A multitude of factors — poor diet habits, stressful lifestyles, aging populations, etc. — is causing chronic diseases like cancer and arthritis to soar, and our twentieth century healthcare delivery infrastructure is simply not designed to handle the surge in these types of ailments. We need far better ways to mine huge volumes of patient data from multiple sources, and to effectively present the critical pieces of information to the right person at the right time to help yield the right decision, all the while ensuring privacy and security. We need ways to improve process flows, to create feedback loops, to establish care “control rooms,” etc. We need ways to monitor (sense) and assist patients’ health, activities, and behaviors in their homes, offices, and churches. We need an entirely new social infrastructure, one that builds off of today’s “connected” world and incentivizes integration and adoption of new technologies, a belief in wellness management (“prevention is better than a cure”), and the role and persuasive effects of one’s social network. And we need to do all of this work in the context of the incredibly complex organizational structures, payment plans, policies, and regulations underlying the healthcare enterprise. Health information technology is not just about electronic medical records (EMRs), in which the Federal government has invested significant resources over the past year (see ongoing programs); it’s also about robotic surgery, telemedicine, home monitoring, Health 2.0, and much more.

But we can’t revolutionize care delivery overnight. To achieve a safe, effective, reliable, and far less expensive system five, 10, or 15 years into the future, we need groundbreaking research now in areas like data management, data mining/machine learning, human-computer interaction, modeling and simulation, software engineering, reliability engineering, process engineering, sociotechnical systems, etc. Yet, to date, Federal investment in health IT research has largely been fragmented.

As we’ve articulated in the white paper, the recent passage of healthcare legislation makes a broad research initiative in this space incredibly timely. There is no better time like the present — and, frankly, with chronic disease on the rise, doctors and hospitals increasingly overburdened, and friends and families lost in an abyss of uncertainty about their loved ones’ conditions and care options, we can’t afford to delay any longer.

As a community, we are calling for a large-scale, comprehensive, coordinated, collaborative, and multi-disciplinary basic research investment by the Federal government. We believe this investment must involve computer scientists, but it should also include allied areas of systems engineering and the social sciences. As these areas are core constituencies of the National Science Foundation, the agency must be heavily involved. (Indeed, NSF’s CISE Directorate just announced a Smart Health and Wellbeing Program for FY 11, which “aims to facilitate large-scale discoveries that yield long-term, transformative impact in how we treat illness and maintain our health”: http://www.nsf.gov/pubs/2010/nsf10575/nsf10575.htm.)

The work can’t proceed without medical practitioners either, as they need to inform the technologies as they are being developed — and consequently the National Institutes of Health, the primary Federal agency for conducting and supporting medical research, must be at the table as well. And there are a whole host of other Federal agencies that should be consulted: the Office of the National Coordinator for Health IT (ONC) and the Agency for Healthcare Quality and Research (AHRQ), which have invested billions in developing and deploying EMRs around the country; the Centers for Disease Control and Prevention as the nation’s public health agency; and the Food and Drug Administration, which must regulate technologies emerging from our nation’s research labs and arriving in hospitals and clinics.

Let’s do something big in health IT today — so that we can enhance the quality and length of life tomorrow. It’s critical for our society, for our economy, and for our success and prosperity as a nation. For more, I encourage you to review the CCC-led white paper.

Broad agenda-setting

During the transition period to the Obama administration, we had the opportunity to feed a number of “white papers” into the transition team’s planning process.  Thanks to the receptiveness of the incoming administration, these white papers had impact far beyond what we had dared to imagine.

Our approach was to focus on the fact that fundamental advances in computer science and computer engineering are essential to meeting the nation’s challenges and achieving the nation’s priorities.  America’s energy future, from transportation to the smart grid, depends essentially on fundamental advances in computer science and computer engineering.  Ditto for the transformation of health care.  Ditto for the future of education.  Ditto for 21st century data-driven discovery — “eScience” — which will be transformational, ubiquitous, and driven by fundamental advances in computer science and computer engineering.

This approach does not position our field a “tool” of other fields, because it is not about applying today’s technology.  Rather, it focuses on the fundamental advances in computer science and computer engineering that will be necessary to meet the nation’s challenges and achieve the nation’s priorities.

This work was done pro bono by a small number of people.  (Committees produce consensus; leaders produce visions.)  And it was carried out as what computer architects would call “speculative execution” — effort devoted in the belief that it might prove to be useful.  (If you wait until someone asks you for something, it’s too late — you need to have it ready!)

Focused agenda-setting

The CCC funds workshops initiated by members of sub-fields who want to chart a future direction.  Some of these have been hugely influential.

A great example is a robotics effort led by Henrik Christensen (Georgia Tech), Vijay Kumar (Penn), Matt Mason (CMU), and others.  This broad community effort, carried out over a period of 18 months, yielded a coherent direction for fundamental research in robotics, a set of “research roadmaps” for the field, and a white paper that is likely to result in a significant federal research initiative during the next fiscal year.

Computing Innovation Fellows

During the 2008-09 academic year it became clear that, due to the economic downturn, many extremely strong Ph.D. graduates would “exit the research game” due to lack of employment opportunities at universities and industrial research labs — sacrificing the nation’s investment in their education, and jeopardizing the nation’s future competitiveness.

Computer science had never had a broad-based coordinated postdoc program, but the Computing Community Consortium, working closely with NSF, was able to establish the Computing Innovation Fellows Project in remarkably short order — from concept to awards in less than six months.  It was NSF’s confidence in CCC as a “proxy” for the computing research community that made this possible.

The CIFellows Project had several unique aspects that we expect to have broad impact.  The first was the “max 2 rule” — at most two awardees were allowed to come from, or go to, any one institution.  (The goal was to establish persistent interactions between diverse institutions.)  The second was an ordering of the holistic quality assessment of candidates:  at each iteration (as the field was reduced from 500+ proposals to 60 awards), members of under-represented groups (women, minorities, particular research areas, etc.) were discussed first.  When the dust had settled, 42% of CIFellows awardees were women!  (To be clear:  gender only influenced the order of discussion!)

Summary

There’s lots more to say, but this is getting long for a blog post.  The bottom line is that a group of community-oriented research leaders can have a profound effect, given the endorsement (confidence and good will) of the research community, and the right environment in Washington.

There are many, many ways in which you can participate.  See the CCC web page for ideas!

The Visions conference was designed to highlight research visions for the future and consisted of invited plenaries and submitted talks. The plenaries were extremely well done.  Ross Anderson spoke about the integration of social issues and computing in the design of increasingly complex systems, using numerous examples from history and economic theory. Nicolò Cesa-Bianchi explored frontiers in machine learning, Jon Kleinberg spoke about the future of social networks, and Barbara Liskov provided a very interesting retrospective on the work that lead to her Turing Award coupled with lessons from this work for the future.

The UKCRC Grand Challenges effort  has been underway since 2002; Sir Tony Hoare and Robin Milner (the conferences began with a very nice tribute to him) started the effort following Hoare’s attendance at CRA’s first grand challenges workshop. The UK effort has been considerably more structured than similar efforts in the US: there is a steering committee, a group of topics was selected, leadership committees were created, funding was obtained for activities and, over time, road maps for research in each area were developed. Status results were presented and the results have been mixed. Some areas, e.g., Dependable Systems Evolution, are seen as quite active and self-sustaining. Others, e.g., Ubiquitous Computing, seem to have faded with research still ongoing but not focused by the grand challenges effort. It is not clear whether the grand challenge model has generated any substantive additional research funding for the selected challenges.

The conference addressed the status of ongoing efforts as well as discussions about new ones including tele-health, IT & Global Climate Change and Computing for 9 Billion People. The steering committee will select which ones to advance;  finding a strong advocate will be a key selection criterion. Interestingly these more recent proposed grand challenges are definitely focused on societal problems rather than computing ones.

Both of these efforts are directly related to the activities of CCC in envisioning and promoting research futures in computing.

(Contributed by Andy Bernat, Executive Director of CRA)

- Translation into other domains of software

- Software engineering practice

- Collaboration issues in FOSS

- Learning and education challenges/opportunities

- Evolution of products, projects, practices and processes

- Research infrastructures

A report from the workshop will be developed in the coming weeks and posted on the CCC Web site.

John L. King, CCC Council Liaison

John L. King, CCC Council liaison

Today’s discussion was structured around four perspectives on FOSS, with moderators, main presenters, and discussants:

Users/Producers: Moderator — Greg Madey (Notre Dame University); Main Presenter — Ralph Morelli (Trinity College); Discussants — Stormy Peters (GNOME Foundation), John Wallin (George Mason University).

Human-Centered Computing: Moderator — Walt Scacchi (UC Irvine); Main Presenter: Chris Kelty (UCLA); Discussants — Charles Schweik (UMass Amherst), Chris Kelty (UCLA).

Social/Behavioral/Economic: Moderator — Kevin Crowston (Syracuse University); Main Presenter — Les Gasser of University of Illinois-Urbana/Champaign; Discussants — Kalle Lyytinen (Case-Western), Shobha Chengalur-Smith (UC Irvine), Pat Wangstrum (IBM Research).

Software Engineering:  Moderator — Megan Squire (Elon University); Main Presenter Tony Wasserman (Carnegie-Mellon Silicon Valley); Discussants — Prem Devanbu (UC Davis),  Audris Mockus (AVAYA Labs).

The Twitter stream is #foss2010   Follow along!

John L. King, CCC Council liaison

The Discovery and Innovation in Health IT Workshop was an attempt to make further inroads on productive collaboration between healthcare and computing, exploring and defining fundamental computing research challenges and opportunities in healthcare IT in both the near- and long-term and identifying a range of “model” proof-of-concept, integrative systems that might serve as motivating and unifying forces to drive fundamental research in healthcare IT.

Highlights of the workshop included plenary presentations by William Stead of Vanderbilt and Richard Bucholz of St. Louis University School of Medicine. Stead  argued that the “increasing complexity and amounts of biomedical information will overwhelm individual experts, leading to the need to move beyond expert-based medicine.”   (For more information see: Beyond Expert-based Practice, William W. Stead, M.D., and John M. Starmer, M.D.  http://courses.mbl.edu/mi/2009/pubs/Fall_Stead_Expert.pdf )

Bucholz, who is a computationally-savvy neurosurgeon and inventor of the StealthStation, a neurosurgical navigational system, described linking the cutting edge (literally) of neurosurgery and computing to create integrated realtime intra-operative delivery of information via navigational systems, images, 3D visualizations, EEG and other information sources.

Chris was particularly interested in the biomedical aspects of the workshop.  He says:
Healthcare and biomedical research have become increasingly intertwined with computing.  The status, goals, and impediments for 21st century biomedicine were well summarized in the 2004 NIH Roadmap. The Roadmap noted that computing has become absolutely essential to progress in biomedicine, stating:  “The success of computational biology is shown by the fact that computation has become integral and critical to modern biomedical research.”

However, the report also noted that both the substantial and substantive challenges biomedical researchers face in embracing and applying cutting-edge computing research, as well as those faced by computing researchers in understanding current and future biomedical computing needs, have inhibited biomedical research:  “Because computation is integral to biomedical research, its deficiencies have become significant limiters on the rate of progress of biomedical research.”

The productive synergies between these two fields can accelerate research in both, but only if we address these challenges through cooperative effort.  The agencies and the communities, in other words, must work together to enhance frontier or cutting edge research at the interface.  The Discovery and Innovation in Health IT Workshop was an attempt to make further inroads on productive collaboration between healthcare and computing, exploring and defining fundamental computing research challenges and opportunities in healthcare IT in both the near- and long-term and identifying a range of “model” proof-of-concept, integrative systems that might serve as motivating and unifying forces to drive fundamental research in healthcare IT.

Let’s hope that the healthcare, biomedical, and computing research communities  take this as a further opportunity to  overcome current roadblocks by moving across traditional disciplinary boundaries and truly engage computing and biomedical researchers.

Beth’s take-away was somewhat different.  She says:

I also attended the Discovery and Innovation in Health IT Workshop.  With so many obvious shortcomings in the current healthcare system, it is tempting to focus on near-term challenges.  In fact the discussions in the press and on Capitol Hill orient to current inefficiencies in the healthcare system as well as the poor health outcomes that stem from misaligned incentives.

However this workshop allowed space for the discussion of long term challenges that, when addressed, could also solve many short-term deficiencies.

As detailed in the NAS report, “Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions,” (http://www.nap.edu/catalog.php?record_id=12572) current health IT is deployed as a transactional system instead of supporting workflow, decision making and collaboration.  Furthermore the practice of healthcare is dramatically shifting along a number of dimensions including:

• the overwhelming cost and impact of chronic disease (e.g. diabetes, heart disease, obesity)
• the abundance of information that is available but not utilized by health care practitioners (sensor data, research reports, population data)
• the advent of new diagnostic techniques, based on genomic data, that could enable disease diagnosis years before the disease is detectable by traditional means.

Many of the breakout groups at the workshop honed in on approaches for patient-centered care, chronic disease management and prevention, and distributed, collaborative care.  These approaches mirror the reality of healthcare now and for the foreseeable future.  They also call for deep and challenging computing research including:

• Ubiquitous computing technologies for chronic disease management, including technologies that enable behavior change
• Workflow and decision support systems that actively incorporate health outcome data
• Security and privacy models for distributed, patient-centered care
• Machine learning techniques to predict future health trends and treatment complications
• Organizational modeling and simulation to anticipate economic repercussions in future healthcare approaches

Contributed by Chris Johnson, Director of the Scientific Computing and Imaging Institute, University of Utah (www.sci.utah.edu) and Beth Mynatt, CCC Member and Director, GVU Center at Georgia Tech (www.gvu.gatech.edu)

Metagenomics is a relatively new field that seeks to understand the
structure and function of the shockingly large number of microorganisms on
our planet.  New technologies permit us to now sequence samples taken from
their environment rather than only those that are cultivated in the lab. For
example, Craig Ventner’s Global Ocean Sampling Expedition has collected water throughout the world’s oceans, captured organisms, and sequenced their DNA. In the initial pilot study alone, nearly 150 new bacteria were discovered through this process.

The science and computing challenges are huge. A single gram of soil
contains approximately one trillion base pairs of DNA. Scientists at the National Institutes of Health recently compared over 100,000 bacterial gene sequences on the human skin and discovered a far larger number of different bacteria living on human skin than had been previously known (Science, May 28, 2009). Sequencing and making sense of these data introduces new computational problems, not merely slight extensions of existing ones.

The potential impacts of understanding these data are huge as well. In the
case of soil, microbial communities have an impact on carbon sequestration
and understanding them may help us with cleaning toxic waste. In our bodies,
microbial cells are estimated to outnumber our human cells by a factor of
ten to one and are important in protecting our skin, digestion, and much
more. Understanding these large microbial communities is therefore likely to
have a positive impact on human health. The NIH has launched the Human
Microbiome Project to support work in this field.

Complete DNA sequences of thousands of organisms are piling up in databases
because of the efficiency of DNA sequencing technologies. Most of this
remains unanalyzed for several reasons. We don’t yet know the right
biological questions to ask. We don’t have all the clever programs that
would actually ask these questions of the computer. And there is now so much
data that many questions totally overwhelm even existing high performance
computers.

Among the computational challenges in this field are the design of new
algorithms and cloud computing technologies. In the National Academies of
Science publication “The New Science of Metagenomics: Revealing the Secrets
of our Microbial Planet”, the authors conclude “What then, will metagenomics
have become, in 20 years? We believe that it too will be a concept-driven
computational science… We can expect, in 20 years, enormous advances on
three fronts – technical, computational, and biological – as well as a host
of specific applications.”

We encourage our community to explore and engage in this and other emerging
fields at the crossroads of biology and computation. This is one of the
exciting areas for 21st century computing.

Contributed by Bill Feiereisen with assistance from Ran Libeskind-Hadas

The third meeting will likely be scheduled for late October, though draft vision/consensus documents are being crafted before this next meeting.  The meeting will held at IBM in Austin, Texas, and will engage leaders from funding agencies as part of the program.

• Transition Team white papers (see them here)
• Library of Congress symposium (transparencies and videos here)
• Computing Innovation Fellows project (blog post here)
• NetSE Research Agenda (blog post here)

See the presentation here (pdf).

Over the past forty years, computer networks, and especially the Internet, have gone from research curiosity to fundamental infrastructure. However, this is no time to rest on the successes of the past. To meet society’s future requirements and expectations the Internet will need to be better: more secure, more accessible, more predictable and more reliable.

In 2008, the Computing Community Consortium charged the NetSE Council with developing a comprehensive research agenda that would support the development of a better Internet. The NetSE Research Agenda report summarizes the findings and recommendations of the NetSE Council.

The intended audiences for the report include members of the computing research community, funding agencies, and policymakers.  The report provides a framework or context within which various targeted research agendas can be moved forward by their communities.  The report is your document (literally hundreds have contributed to it in various ways), and it is a living document – comments are earnestly solicited, as indicated on CCC’s NetSE activity web page.

Read the full report here!

Many thanks to Ellen Zegura for seeing this activity through to a successful conclusion!

Videos of the presentations (as well as slides) are now available on the symposium website.  See http://www.cra.org/ccc/locsymposium_slides.php for the complete agenda with individual links, or see our YouTube channel, http://www.youtube.com/computingresearch.

Talks at the Symposium included:

• Introductory Session
  • Ed Lazowska (University of Washington), “Changing the World”

• Session 1: The Internet and the World Wide Web
  • Alfred Spector (Google), “Why We’re Able to Google”
  • Eric Brewer (UC Berkeley), “The Magic of the ‘Cloud’: Supercomputers for Everybody, Everywhere”
  • Luis von Ahn (Carnegie Mellon University), “Human Computation”

• Session 2: Evolving Foundations
  • Barbara Liskov (Massachusetts Institute of Technology), “Security of Online Information”
  • Daphne Koller (Stanford University), “Learning to Improve Our Lives”
  • Jon Kleinberg (Cornell University), “Global Information Networks”

• Session 3: The Transformation of the Sciences via Computation
  • Larry Smarr (UC San Diego), “Supercomputers and Supernetworks are Transforming Research”
  • Chris Johnson (University of Utah), “Computing and Visualizing the Future of Medicine”
  • Gene Myers (Howard Hughes Medical Institute), “Zooming In On Life”

• Session 4: Computing Everywhere!
  • Deborah Estrin (UCLA), “Sensing Everywhere!”
  • Pat Hanrahan (Stanford University), “Pixels Everywhere!”
  • Rodney Brooks (Massachusetts Institute of Technology), “Robots Everywhere!”

http://www.cra.org/ccc/locsymposium_slides.php

Videos of all talks will be available soon.

Previous posts describing the symposium are available here and here.

Many thanks to our speakers for preparing and delivering such wonderful talks, and for making their materials available to the community at large.

Inspiration for the program came from a large number of responses from the computing research community to two November CCC blog posts — this was your symposium!

Each of the talks was superb.  Honestly, in 35 years in the field, I’ve never before spent a day with such uniformly high quality of content and presentation.  It was remarkable.  The videos of the 20-minute talks will be a great resource for all of us.

My introductory talk (pdf) provided a quick overview of the impact and promise of the field, as well as a peek at the day’s program.  I drew upon a recent New York Times article describing a Wharton School assessment of “the top innovations of the last 30 years” (more than half of which were direct results of computing research!) as well as a recent CSTB study “Assessing the Impacts of Changes in the IT R&D Ecosystem” (which described a day without information technology as “a day the Earth stood still”).

My closing remarks summarized both the content and the messages of the day-long symposium.  I won’t repeat Susan’s earlier summary of the content, but here are a few additional highlights:

• Alfred Spector commented that “Google did not arise through spontaneous generation in a garage in Palo Alto — it drew upon a broad set of computing research advances.”
• A number of the talks — Luis von Ahn‘s, Jon Kleinberg‘s, Rodney Brooks‘s, probably others — alluded to emerging “hybrid systems”:  humans + computers.
• Daphne Koller presented a terrific catalog of the successes of machine learning.
• Gene Myers asserted that “computation is the bottleneck in every [modern molecular biology] project” — a perfect bookend to Larry Smarr‘s session-leadoff talk on the transition to data-intensive science.
• Chris Johnson made it clear that in the past decade, modeling and visualization have become valuable tools in advanced surgical practice — M.D.’s are beating down his door to obtain access.
• Pat Hanrahan presented neat timelines of the transformation of all media — publishing, audio, photography, and video — from analog to digital.
• Rodney Brooks ended the technical sessions on a cautionary note:  The future of robotics is robots that operate in unstructured environments.  America has a wide lead now in this field.  But once, we led in manufacturing robotics, and we allowed that lead to slip away.  Will we allow that to happen again?

That’s a good jumping-off point for the messages of the day.  Here’s my list:

• Computing research truly has changed the world.
• A rich and complex ecology — involving government, academia, and industry — has made America the world leader.
• Research has laid the foundation — you can find federally-funded university-based research at the heart of essentially every billion-dollar sector of the IT industry.
• It consistently takes 10 or 15 years from “research breakthrough” to”billion-dollar sector.” So you need patience — there’s no such thing as “just-in-time research.”
• Often, “products” in IT are created by synthesizing multiple advances — unlike biomedicine, where a single patent can yield a blockbuster drug.
• Often, old ideas gain new life.  We’ve had recent breakthroughs in search and in machine learning, but each traces its roots back at least 40 years.
• While computing research often is motivated by a “strategic objective” — we see a practical value if the research succeeds — we’re often not very good at predicting what the greatest impact of our innovations will be.  Serendipity plays a huge role.  Any attempt to decide early-on what research is “important” is likely a losing proposition.
• While much of the exciting computing research today is interdisciplinary and collaborative, it’s important to have a balanced portfolio:  core + interdisciplinary, single-investigator + team, etc.

The bottom line:  We have an extraordinary track record — America has an IT R&D ecosystem that again and again leads to massive transformations.  And the next ten years can be our golden age:  on March 25th we heard about some amazing recent accomplishments, and we heard from some extraordinary young people (as well as some extraordinary not-so-young people) who are driving the field forward.  The opportunities for impact are greater than they have ever been.  Go out and change the world!

– Ed Lazowska

I finished The Mystic Arts of Erasing All Signs of Death by Charlie Huston just before the City Archives collapsed in Cologne, Germany, on March 3. I soon found myself at my 11th disaster, but unlike Webb, the protagonist who must come to grips with the events that led him to a janitorial job cleaning up trauma sites, I was clear on why I was there standing in the rain. I was there in the hope that we could make a difference with technology — that we could enable the fire rescue teams to save a life, prevent a responder’s death, or even bring a family’s agonizing wait to closure. Or to help the structural engineers discover and document What Went Wrong. And, if not that, learn something for the next time.

We accomplished option C at least.

Let me offer this photograph as the spoiler alert for my personal blog (rescuerobotics.blogspot.com) which has details, history of robots for building collapses, and some pictures and video. In the picture, I’m on the right, down at the mid-level of the collapse (there were two more stories of flooded or damaged subway structure below us) with the Cologne Chief of the Fire Department, the head of special operations, and the safety officer (all wearing reflective bunker gear). The photo was snapped a few minutes after we had reached the conclusion that robots could not be used. In the photo we are chatting about the collapse, the dangers, the sequence of events that had led to the catastrophe and resulting challenges before clambering up the scaffolding to the safer street level.

Standing there in Germany, I couldn’t help but be reminded of all the ways computing could be applied. Robots. Cyber-physical systems. Sensors to penetrate the rubble and algorithms to process and mine the data. Reliable and secure high bandwidth wireless networks. Optimal resource allocations and scheduling. Mapping and 3D surface reconstruction. Sketch-based and multi-modal interfaces to tablet PCs to make it easier for the experts to express their knowledge. Social networking to help the displaced residents figure out how to adapt, where their friends had been relocated to, what was really going on.

Looking again at the photograph brings me back to the The Mystic Arts. I was particularly touched as to how at the end of the novel Webb comes to view his work as a sacred duty. The disaster “lifecycle” of prevention, preparedness, response, and recovery is a lot like trauma work — it is infrequent, not well-funded or understood, very challenging, and ultimately inevitable.  Standing there in Germany, I glimpsed the journey ahead for the computing community as we, too, embrace the difficult and necessary, and make the field of emergency informatics our sacred duty as computing, well applied, can help erase all signs (and maybe the causes) of death.

– Robin Murphy is a Professor at Texas A&M University, and one of the newest members of the CCC Council. Previously, Robin’s robots also conducted search-and-rescue operations at the World Trade Center shortly after 9/11.

I think that this symposium is really important because with a new administration in Washington, we have people who appreciate the importance of fundamental research. If we increase the size of the funding pie, all of us will benefit. The best way to increase the size of the computing research part of the pie is to link advances in computing research to advances in other fields and the larger society.

That is what the March 25 symposium is about. With the cast of speakers we have lined up and the number of people from government agencies and Congress who will be attending, we have a great chance to make a difference. Check out the program; we had to keep the invitation list small due to the location, but all the talks will be recorded.

– Greg Andrews

It’s certainly exciting to see core computer science issues featured so prominently in the press! Indeed, this article has generated quite a bit of discussion in the research community. For example, while acknowledging that a new network architecture would certainly play an important role in improving security, Purdue’s Gene Spafford writes on his CERIAS blog, “Do we need a new Internet? Short answer: Almost certainly, no.” (Gene tells me that he will be interviewed on this topic on C-SPAN’s Washington Journal, airing at 9:30am on Saturday, February 21.) UCSD’s Stefan Savage is largely in agreement, saying that “the network is by and large the smallest part of the security problem” and that “at a technical level the security problem is really an end-host issue, coupled with an interface issue — lots of power given to lots of different pieces of software whose couplings present opportunities to bad guys that aren’t anticipated, at a social level its a human factors issue.” The bottom line is that, outside of resource management (that is, controlling DDoS) and attribution/accountability, the main sources of security risk are at the end points — a key point missed in the NY Times article. Peter Freeman perhaps puts it most plainly:

To be succinct, although technical improvements are clearly needed, a large part of the security issue comes back to people, not technology. If we could figure out how to educate people so they don’t respond to pleas from Nigerians who need to transfer money or they don’t leave their passwords on post-its or never install the frequent security patches that are issued, we could make huge improvements immediately.

That’s not to say, however, that reinventing some aspects of networking isn’t an important research goal. Peter Freeman, while he was the director of NSF’s computer science (CISE) division, was instrumental in helping to launch the GENI Project in 2004, with the goal of developing an experimental platform for exploring truly reliable and higher capacity networks. For Freeman and others, new approaches to networking were deemed an important area for government investment because of the basic nature of the research problems involved.

Mounting a global-scale effort such as GENI has been a major challenge for the computing research community, perhaps similar to what the astronomy community goes through when it decides to develop large telescopes. But the initiative has already had several ripple effects. Guru Parulkar, who was the NSF program manager for GENI at the start, went to work with Nick McKeown and helped start the Clean Slate Project mentioned in the NY Times article. The GENI effort also put Princeton’s Larry Peterson in the middle of things, as the PlanetLab Consortium was one of the most influential early inspirations for GENI. And now, a much broader visioning effort in Network Science and Engineering, or NetSE, supported by the Computing Community Consortium (CCC), is defining the critical research questions in a wide range of network-related areas.

As for GENI itself, significant progress on development of a prototype has been made, coordinated by a GENI Project Office (GPO) and involving a large number of academic researchers. BBN’s Chip Elliott says that a version of the testbed will be available for early testing in a matter of months, “which will allow researchers to investigate many core networking research questions, some of which are the thorniest questions for Network Science and Engineering, upon the earliest end-to-end prototype of GENI.” Ellen Zegura, Georgia Tech professor and NetSE Council Chair, cites the importance of this development, saying “For me, the deep technical issues of security and privacy are at the heart of the GENI effort, and one of the main reasons for developing it.”

The demand for better security grows with the public’s dependence on computing and networking. As Chip Elliott states:

Would our lives improve if all aspects of the Internet were firmly bound to real-world personal and organizational identities? Might total public transparency reduce crime and misbehavior – in short, might less privacy lead directly to more security? Is privacy already a vanishing concern, fated to disappear in a few years without widespread regret?

Careful thinking will illuminate these issues — particularly if coupled to a vigorous program of experimentation.

This, in a nutshell, is what the NetSE and GENI initiatives aim to address.

– Peter Lee

The United States of America has steadily fallen further and further behind Asian and European nations with respect to broadband penetration and related services. This is impeding the development of new consumer applications (and related new industry and services) and limiting communications in an economy where knowledge exchange is vital in order to be to be a major player of the emerging , seamless and unobstructed global market. Reversing this trend may be of high interest to the incoming administration, but the viability of extending broadband is dependent on the deployment of new high bandwidth and high value applications that (a) will justify the investments required and (b) will contribute digital solutions to many of the key societal problems in this Energy-Climate Era (as recently identified by Thomas L. Friedman in his book Hot, Flat and Crowded) such as growing demand for ever scarcer energy supplies and natural energy, rapid and accelerating biodiversity loss, and disruptive climate change.

In 1997, Jaron Lanier, at the time the chief scientist of Advanced Networks and Services, started the National Tele-Immersion Initiative, as a coalition of research universities studying advanced applications over Internet2. We never capitalized on this initiative in United States. Instead, virtually all major advances in the commercial design and development of 3D multimedia input and output devices such as 3D stereo cameras, 3D displays, integrated solutions for the next generation of home entertainment systems were undertaken abroad. If we look at the corporate landscape of multimedia technology and its integrated multimedia solutions, they come mostly from Asia (e.g., NEC, Panasonic, Sony, FXPal, Samsung) and Europe (e.g., Phillips, Thomson). Swift action is needed to ensure American universities and industries seize the academic and business leadership of the next generation of tele-immersive systems, the 4D Immersive Holographic Spaces.

4D Immersive Holographic Spaces will be joint multi-view multimedia-rich spaces where people can immerse themselves in their physical full body size into a joint cyber-physical space with other people, and execute physical activities (e.g., physiotherapy rehabilitation), walk around people and observe detailed full-body social behaviors and communication cues of people in real-time, as if they were co-located in the same room, even though they are geographically distributed and thousands of miles apart. The impact of such systems would be dramatic, contributing to the increase of innovative economic opportunities, to the “green energy” efforts, and to the decrease of gap between regions of “have” and “have-not” experts. With respect to innovation leadership, venture capitalists will for the first time be able to interact with entrepreneurs located thousands of miles away as if they were next door. Our nation’s ability to find and grow new and emerging high-technology high-quality job-creating companies would extend to all regions of America. In health care, new services based on these cutting edge information systems could be delivered to our rural areas. A physiotherapist based in Washington would be able to provide rehabilitation assistance to multiple remote patients after heart-attack in neighboring regions and a wheelchair basketball coach in Illinois could inspire and train wheelchair children in Montana to play the sport. The children of the men and women of our armed forces would be able to explore the Amazon forest with their parents in a virtual world or simply learn basic values from their parents by bringing them together in their (virtual) home. All of these scenarios are dependent on the ability of 4D Immersive Holographic Spaces to deliver rich visible social cues and multi-view capture of human/group behaviors.

America can lead in the area of broadband information-rich immersive spaces if major investments are made to develop and build national tele-immersive infrastructures. We can then ensure US companies deliver innovative applications and services solutions with our academic institutions as key partners in addressing the research and development challenges. Advances in real-time computer vision, real-time computer graphics, integration of speech, vision and tactile sensory information, dynamic and task-dependent signal compression, and broadband wired and wireless networking with advanced stream-based and multi-view distributed and operating systems and architectures will be needed for the future tele-immersive systems. It is imperative that we move boldly and commit ourselves to this effort.

What is a “better Internet”? The current Internet has been a remarkable success, providing a platform for innovation that far exceeds its original vision as a research instrument. It is well documented that the Internet has transformed the lives of billions of people in areas as diverse as education, healthcare, entertainment and commerce. Yet many of these successes are threatened by the increasing sophistication of security attacks and the organizations that propagate them. A materially more secure Internet would be “better”. Further, billions of people remain untouched by the advantages of the Internet; Internet World Statistics puts worldwide average Internet penetration at about 22% in mid 2008. An Internet that affordably reaches the other 80% of the world population would be “better”.

Beyond security and accessibility, there are other areas where limitations of the current Internet are significant. The Internet usually works pretty well, but every user has experienced inexplicable periods of degraded performance or outright non-function. The current Internet provides no visibility to end-users and shockingly little visibility to network managers and operators to support understanding, adapting to and fixing reliability problems. Such limitations require lay people spend their leisure time as network systems administrators and companies to spend heavily in network operations. Further, the lack of performance reliability prevents the Internet from advancing to become a truly dependable, critical infrastructure. Indeed, current societal reliance on the Internet for critical functions is disproportionate to our ability to deliver a high degree of dependability. A more predictable Internet would be “better”.

The Internet embeds societal values in ways that are often implicit and not well understood. For example, the Internet is “open”, usually intended to mean that anyone can join the network by implementing the public protocol IP. In principle, users can run any application on the Internet, without limitation imposed by the network protocols. Open networks promote organic growth, but suffer from a lack of mechanisms to vet or bar participation. Issues of trust and individual accountability are confusing. As the well-known cartoon says, “On the Internet, no one knows you’re a dog.” An Internet that contains support for identity would be “better”.

The research community is poised to dramatically advance the agenda of building better networks through advances in both empirical design methodology and systematic design methodology. We have an approach to support large-scale and flexible experimentation based on programmability of devices and federation of multiple test-beds. We have a nascent mathematical framework for understanding architectural features and underlying principles. The time is right to advance and link both methodologies to realize better networks.

– Ellen Zegura

“Congress is now debating the American Recovery and Reinvestment Act of 2009. Included in this package is over 10 billion dollars for science facilities, research, and instrumentation.

“The reason for this inclusion is simple: today’s research is tomorrow’s infrastructure.

“When our nation faces immediate challenges, the feasible solutions depend upon the ideas, resources, and designs that are “on the shelf,” ready to deploy …

“Increasingly, information technology is the cornerstone of America’s infrastructure. Today’s information technology research is a cornerstone of tomorrow’s infrastructure.”

Read the full editorial here.  A set of white papers describing the role of computing research in meeting the challenges of the 21st century is available here.

Now, the full story:

The CCC’s mission is “to foster exciting new research visions in the computing community which attract support.” Looking back at what has transpired over the past year, community participation has been tremendous. Many dozens of people have stepped up to propose workshops, make presentations, write articles for this blog, and chip in with thoughtful feedback and ideas. It’s been productive and, well, fun.

Of course, the name of the game is to turn research visions into reality, and one of the core strategies for doing this is to “improve public and policymaker understanding of the importance of computing and computing research in our society”. This seems particularly important right now, as our nation makes a historic transition, hopefully ushering in a new era in the government’s approach to research support.

Without really knowing what kinds of results we would get, we put out a challenge to a small number of people to write very briefly (we asked for two pages) on “computing research initiatives for the 21st century.” What does the new government need to know about the value of computing research? What are some of the most promising and exciting research opportunities in the field? What computing capabilities are critical for the nation today and into the future?

Well, the response has been tremendous. A sample of what we received is now posted on the CCC web site at http://www.cra.org/ccc/initiatives. There are essays on the central role that computing research has in our economy, ideas for research/education infrastructure, “re-envisioning DARPA”, and proposals for research initiatives in personalized medicine, transportation, “big data” computing, computer architecture, networking, cyber-physical systems, and more. WIth this treasure trove of thoughtful inputs, we are now using available channels and the CRA and CCC’s resources to get these noticed by as many policymakers as possible.

We have been so heartened by the response that we are now talking about having a more organized process for soliciting and publishing these sorts of idea-pieces. Stay tuned here and on the CCC web site for more details, some time early in 2009. We’ll also be asking some of the authors of these writeups to post followup discussion pieces on this blog.

Again, thanks for all of your support and participation. 2009 is looking like a truly exciting year.

– Peter Lee and Ed Lazowska

–

The CCC blog has published a couple of articles on the multi-core challenge, all emphasizing the difficulty of making parallel programming prevalent and, hence, the difficulty of leveraging multi-core systems in mass markets. The challenge is, indeed, significant and requires important investments in research and development; but, at UPCRC Illinois, we do not believe that the sky is falling.

Parallel programming, as currently practiced, is hard: Programs, especially shared memory programs, are prone to subtle, hard-to-find synchronization bugs and parallel performance is elusive. One can reach two possible conclusions from this situation: It is possible that parallel programming is inherently hard, in which case, indeed the sky is falling. An alternative view is that, intrinsically, parallel programming is not significantly harder than sequential programming; rather, it is hampered by the lack of adequate languages, tools and architectures.  In this alternative view, different practices, supported by the right infrastructure, can make parallel programming prevalent.

This alternative, optimistic view is based on many years of experience with parallel programming. While some concurrent code, e.g., OS code, is often hard to write and debug, there are many forms of parallelism that are relatively easy to master: Many parallel scientific codes are written by scientists with limited CS education; the time spent handling parallelism is a small fraction of the time spent developing a large parallel scientific code. Parallelism can be hidden behind an SQL interface and exploited by programmers with little difficulty. Many programmers develop GUI’s that are, in effect, parallel programs, using specialized frameworks. Parallelism can be exposed using scripted object systems such as Squeak Etoys in ways that enable young children to write parallel programs. These examples seem to indicate that it is not parallelism per se that is hard to handle; rather it is the unstructured, unconstrained interaction between concurrent threads that result in code that is hard to understand both from a correctness and performance view, hence hard to debug and tune.

The state-of-the-art in parallel programming is what sequential computing was several decades ago. A major reason for this situation is that parallel programming has been an art exercised by a group of experts whose small population did not justify major investments in programming environments aimed at making their life easier. This reason disappears as parallelism becomes available on all platforms. Furthermore, we can make faster progress now because we understand well the principles it takes to make programming easier — principles such as safety, encapsulation, modularity, or separation of concerns; we also have more experience in developing sophisticated IDE’s.

What will it take to bring these principles of computer science to parallel programming? It will require a broad based attack across the system stack. As has been said in these blogs, we need research in languages, compilers, runtime, libraries, tools, hardware … What has not been said explicitly is that none of these areas are likely to produce the silver bullet on their own. The solution that will work eventually will be one that brings together technologies from all these areas to bear on each other. However, we do not have the luxury of doing this via incremental and reactive changes over decades. The research truly needs to be interdisciplinary and the idea of co-design needs to be internalized. Unfortunately, the mainstream systems community has all but abandoned this mode of research in the last several years. Language researchers are locked into mechanisms that will only be supported by commodity hardware and hardware researchers are locked into a mode that requires supporting the lowest common denominator software. It is imperative that we break out of these shells and get the research community into a mindset that we are truly looking to define a new age of computing — a mindset that nurtures research where a clean system slate is an acceptable starting point.

The sky is not falling, but the ground is shifting rapidly. The multi-core challenge requires a concerted effort of academia and industry to generate new capabilities. We are confident that in the future, as in the past, new capabilities will breed new applications. Multi-core parallelism can be leveraged to develop human-centered consumer products that provide more intelligent and more intuitive interfaces through better graphics and vision, better speech and text processing and better modeling of the user and the environment.

The task of providing better performance is shifting from the hardware to the software. This is an exciting time for Computer Science.

Marc Snir
4323 Siebel Center, 201 N Goodwin, IL 61801
Tel (217) 244 6568
Web http://www.cs.uiuc.edu/homes/snir

• The Industrial Revolution of Data. Today’s world-wide web remains a staggering tribute to the typing abilities of the human race. But even with a growing global population, typists are not a scalable source of bit-production going forward. We are entering an era where the overwhelming majority of information will not be hand-crafted. It will be stamped out by machines: software logs, cameras, microphones, GPS transceivers, sensor networks, RFID readers, and so on. This is inevitable. It has already begun to change the computing marketplace: most organizations of size now realize they can afford to save and mine all their logs, and are looking for inexpensive ways to do so. The startup world has responded with a flurry of parallel database and data analytics companies.
• The Crisis of the Three C’s: Coders, Clouds and Cores. Meanwhile, it’s no news that software development is far, far too difficult. In his Turing Award talk a decade ago, Jim Gray identified radical improvements in programming among his 13 remaining long-term challenges for computing — alongside passing the Turing test and building Vannevar Bush’s Memex. What’s changed on this front since 1998 is the rapid rise of parallelism that my colleagues have been blogging about here. Cloud computing infrastructure, with its “shared-nothing” clusters of machines, demands parallel and distributed programs today. Manycore architectures will demand parallelism at a finer grain in the next few years. The pressing need for parallel software — and armies of fluent software developers to build it — raises both the difficulty and the stakes of the Grand Challenge that Jim Gray highlighted in 1998.

Given this background, what excites me these days is that the trend may bring some new solutions to the crisis, in a surprisingly organic way. 

For over twenty years, “Big Data” has been a sustained bright spot in parallel computing. SQL has been a successful, massively parallel programming language since the late 1980′s, when Teradata (a survivor that evaded Dave Patterson’s Rolls of the Dead) first commercialized parallel database research from projects like Gamma and Bubba. In recent years, SQL has been joined by Google’s MapReduce framework, which is bringing algorithmicists into massive data processing in a way that SQL never did. Both SQL and MapReduce will likely thrive, and may well converge: two parallel database startup companies recently announcedintegrated implementations of SQL and MapReduce. (Full disclosure: I advise Greenplum, one of those companies.)

SQL and MapReduce programmers do not think much about parallelism. Rather than trying to unravel an algorithm into separate threads, they focus on chopping up sets of input data into pieces, which get pumped through copies of a single sequential program running asynchronously on each processor. In parallel programming jargon, this kind of code is sometimes dismissively referred to as being “embarrassingly parallel”. But very often, the simplest ideas are the most fertile. Programmers “get” these approaches to parallelism. And remember: the Coders are part of the Crisis of the Three C’s, and the key is to make lots of them happy and productive.

But can those programmers lead us anywhere interesting? The most intriguing part of this story is that in the last 5-10 years, the set-oriented, data-centric approach has been gaining footholds well outside of batch-oriented data parallelism. There has been a groundswell of work on “declarative”, data-centric languages for a variety of domain-specific tasks, mostly using extensions of Datalog. These languages have been popping up in networking and distributed systems, natural language processing, compiler analysis, modular robotics, security, and video games, among other applications. And they are being proposed for tasks that are not embarrassingly parallel. It turns out that focusing on the data can make a broad class of programs simpler — much simpler! — to express.

Networking and distributed coordination protocols are one good example. They run in parallel, and are themselves a key to cloud services. In our work on Declarative Networking over the last years, we showed that a wide range of network and distributed coordination protocols are remarkably easy to express in a data-centric language. For example, our version of the Chord Distributed Hash Table (DHT) protocol is 47 lines of our Overlog language; the reference implementation is over 10,000 lines of C++. (DHTs are a key component of cloud services like Amazon’s Dynamo.) Meanwhile, graduate students at Harvard prototyped a simple version of the tricky Paxos consensus protocol in an alpha edition of Overlog in 44 rules. (Paxos is a key component in cloud infrastructure like Google’s GFS file system and Chubby lock manager.) We have other examples where our declarative programs are line-for-line translations of pseudo-code from research papers. These are the kinds of scenarios where the quantitative differences are best captured qualitatively. You can print out our Chord implementation on one sheet of paper, take it down to the coffee shop, and figure it out. Doing that with 10,000 lines of C++ would be a superhuman feat of Programmer-Fu, and a big waste of paper.

Machine Learning is another area where data-centric declarative programming seems to help with parallelism and distribution. A group at Stanford pointed to a range of standard machine learning tasks that can be expressed almost trivially as MapReduce programs, without any requirement for parallel programming expertise. More deeply, a number of the fundamental algorithms driving Machine Learning center on “message-passing” algorithms like Belief Propagation and Junction Trees that work on a computational model of explicit dataflow, rather than shared memory. Research in ML over sensornets showed how to overlay that logical communication onto a physical network. And these inference networks — much like DHTs — turn out to be a good fit to Overlog. (Distributed Junction Trees in 39 rules, anyone?) The Dyna language is another good example, with a focus on (currently single-node) Natural Language Processing.

I’ll be the first to admit that Datalog syntax is horrible, and it is not a reasonable language for developers. There is much to be done before adoption of complex data-centric languages can occur. But what excites me here is that the main positive trend in parallel programming — the one driven by the Industrial Revolution of Data, the one with programmer feet on the street — that trend feeds into this promising new generation of much richer data-centric languages. If MapReduce is the boot camp for a next round of parallel languages, those languages are likely to be data-centric. And there’s growing reason to believe that the data-centric approach will suit a wide range of tasks.

– Joe Hellerstein is a Professor of Computer Science at the University of California, Berkeley. His research focuses on data management and networking.

Thanks for the opportunity to update the community on what has been happening recently with the Network Science and Engineering (NetSE) effort, from my perspective as chair of the NetSE Council.

Let me explain my take on NetSE with an anecdote from my Georgia Tech colleague Mike Best based on a recent trip he made to Africa. Mike and his group met with a group of chiefs of the Acholi people in Northern Uganda. This is an area that has suffered through profound conflict and lacks for essentially any communication technology. Mike and his team wanted to engage in participatory design to understand the existing communication needs, unmet needs and requirements, and latent requirements.

They were very cautious not to influence the conversation towards modern communication technologies so they did not mention specific systems. But after about thirty minutes of this exercise one of the chiefs finally stated, “We want the internet. Unless you have something better.”

To me, NetSE is about the potential for something better. That isn’t to take away from how incredible the Internet is, but that success has led to a dependence on an infrastructure that we understand surprisingly little about. Figuring out what “better” means and how we might get there is a challenge that is intellectual, economic, political and social. In other words, hard, but incredibly important.

The last couple of months have been busy for the NetSE community. Five workshops and meetings have taken place since mid-June covering Network Design and X, where X has been Network Science, Societal Values, Theoretical Computer Science, Behavioral Economics, and Network Engineering. The goal of these activities has been to add to all the good work on research opportunities done under the auspices of GENI, but without the yoke of justifying a large facility.

NetSE is shaping up to be strongly disciplinary AND interdisciplinary. There remain major challenges and opportunities in the core disciplines of networking and distributed systems, as well as across disciplines in and out of CISE. For example, technology advances are producing the ability to program all the way down to the photon or RF wavelength. How can and should future networks take advantage of programmability at this extreme? In the interdisciplinary vein, there are important and exciting opportunities at the intersection of human behavior and network behavior. How should home networks be structured so that mere mortals can deploy and manage them?

Over the next couple of months, we will be synthesizing the output of the various activities into a NetSE research agenda that will include recommendations to funding agencies about what is needed to advance the agenda. You can watch for updates on the NetSE page hosted by the CCC at www.cra.org/ccc/netse.php.

– Ellen Zegura is Professor and Chair of Computer Science, School of Computer Science, College of Computing, at the Georgia Institute of Technology.

–

For over thirty years, we have watched the great cycle of innovation defined by the commodity hardware/software ecosystem — faster processors enable software with new features and capabilities that in turn require faster processors, which beget new software. The great wheel has turned, but it no more, as power constraints and device physics now limit the performance achievable with single microprocessors. Multicore chips — those with multiple, lower power processors per chip — are now the norm. Moreover, current multicore chips (those with 4-8 cores/chip) are but the beginning. We can expect hundreds of cores per chip in the future, with diverse functionality (graphics, packet protocol processing, DSP, cryptography and other features).

The software research challenge is clear — developing effective programming abstractions and tools that hide the diversity of multicore chips and features while exploiting their performance for important applications. Hence, we need a vibrant community of researchers exploring diverse approaches to parallel programming — languages, libraries, compilers, tools — and their applicability to multiple application domains.

Microsoft researchers are investigating all of these approaches, from coordination languages for robots and distributed systems to mobile phones to desktops and data center clouds. To engage the academic community, Microsoft funds multicore research projects and many sites, and we have partnered with Intel to fund the Universal Parallel Computing Research Centers (UPCRCs) at the University of California at Berkeley and the University of Illinois at Urbana-Champaign.

As Richard Hamming famously noted, “The purpose of computing is insight, not numbers.” In that spirit, I believe our research challenge is to break free from the limitations of the desktop metaphor and exploit the ever greater performance of multicore chips to create new human-computer interaction metaphors that are more natural and intuitive. This will require new approaches to parallel computing education and increased collaboration with researchers in application domains.

As an example, consider one possible future — “spatial computing” — where real-time vision and speech processing, coupled with knowledge bases, distributed sensors and responsive objects, enhance human activities in contextually relevant ways while remaining otherwise unobtrusive. Such an infosphere would adapt to its user’s needs and behavior and move seamlessly across home, work and play.

Multicore brings enormously interesting intellectual challenges and the opportunity to rethink much of how we approach computing.  Let’s embrace the opportunity!

– Daniel Reed is Microsoft’s Scalable and Multicore Computing Strategist and a member of the President’s Council of Advisors on Science and Technology (PCAST). Contact him at reed@microsoft.com or his blog at www.hpcdan.org

–

Multicore (parallelism) represents a fundamental challenge and change for all of computing and computer science. It represents the fundamental constraints of physics — nature loves parallelism — surfacing and interacting with some fundamental tenets of computing. We have formulated our theory of computation and complexity primarily on sequence — in control and state. Fundamental physics (and consequently circuits and architecture) which makes parallelism fundamentally cheaper is now challenging us to broaden the foundation of computing with parallelism as a first class element. I believe that as a research community, this is a first-order challenge to respond — in nearly all disciplines of computer science. First and foremost, this is a major intellectual challenge to the computer science community to “reinvent” or at least broaden computer science in this way. Second, this is a major educational challenge, where students we are training today to think about “Computer Science founded on sequence” are being launched into a world of parallelism. For their benefit, we must mount a rapid response in pedagogy and curriculum to ensure these students emerge armed to deal with the future of computing in their careers.

Now, let me turn to research funding in parallelism — which is a critical need in all areas from architecture, runtimes, compilers, programming languages, algorithms, and theory. We need major increases in funding and research activity in all of these areas. Governments must take the primary role in funding research in information technology for the long term economic development and societal well-being. We would like to see aggressive large-scale funding of long-range research in parallelism, and that the fruits of that research be made broadly available for commercialization. In the U.S., DARPA has a long track record of funding such research in IT, but such investment has decreased in recent years. We would like to see it increase both in DARPA, as well as other parts of the US government, and yes around the world. History has proven that only governments are able to invest in this type long-term general economic development, and it is critical that the research outputs be generally available for society at large to benefit — not just a small population of gatekeepers. It is great to see this vision being pursued in many regions around the world.

At Intel, we depend heavily on a broad range of science and engineering research pursued by the global academic community. Many of the innovations we commercialize were first conceived in universities — often many years before their practicality — and we have contributed additional innovations and refinements to bring them to the broadest swath of society possible. We strongly support (and contribute our time, money, and leadership to) the health of the research and innovation community globally. We have made significant investments in education (multicore curriculum and training) and research (research grants, Universal Parallel Computing Research Center with Microsoft) for parallelism, and continue to encourage others to join us in doing so.

– Andrew Chien

– To see the first article in this series, click here.

As I mention on my personal blog (at http://csdiary.org), this points out a somewhat strange aspect of computing research, namely that there isn’t much computing research in the major core-science publications. I’m thinking specifically of Science magazine, Nature, and PNAS. In fact, I took a quick scan over the past 5 issues of Science and Nature.  Over those issues, in Science one sees 35 research articles and reports in the biology and medical science areas, 14 in chemistry/materials, 10 in earth and atmosphereic sciences, 5 in astronomy and astrophysics, and several in physics, psychology, and archeology. Only one article in computer science!

In Nature, the situation is even more stark. In the last 5 issues we see 11 research articles in biology, 2 in chemistry, 1 in astrophysics, and 1 in psychology. None in computer science.

Why should we care about this? Well, lately the computing research community has become very concerned about its “image”, particularly in the lay public (including, notably, the US Congress). Yes, we want people to know the full impact of computing, the range of jobs and activities the computing professionals are involved in, and the great economic benefits the come from our research. But we also need, in the interests of public education and our image, to explain computing research to the world’s science scholars. Doing so not only puts our research to a good test, but it also helps to cast an aura of intellectual respectability that would undoubtedly contribute positively to the image of the field.

There could be important consequences within the federal government, too. I asked Peter Harsha, the director of government affairs for the CRA, what he thought about this. Here is what he said:

I think all three [Science, Nature, PNAS] generate news in the more mainstream press that gets noticed by Members of Congress and Administration folks. So while most policymakers and their staff generally don’t read the periodicals directly, the noteworthy stuff they publish finds its way into the NY Times, WSJ, or Washington Post, which quickly gets policymaker attention.

I think all three publications have a good track record of generating that buzz in the mainstream press (Science and Nature, especially).

As we as a community work on getting our government to step up its support of basic science research, to what extent will our representatives include computer science and engineering? While computing will be hard to forget in any serious discussion about funding priorities, putting ourselves “front and center” in these sorts of publications should help not only the cause of computing research but also the large cause of scientific research.

– Peter Lee

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Since the first commercial computer in 1950, the information technology industry has improved cost-performance of computing by about 100 billion overall. For most of the last 20 years, architects used the rapidly increasing transistor speed and budget made possible by silicon technology advances to double performance every 18 months. The implicit hardware/software contract was that increases in transistor count and power dissipation were OK as long as architects maintained the existing programming model. This contract led to innovations that were inefficient in transistors and power but which increased performance. This contract worked fine until we hit the power limit that a chip could dissipate.

Computer architects were forced to find a new paradigm to sustain ever-increasing performance. The industry decided that only viable option was to replace the single power-inefficient processor by several more efficient processors on the same chip. The whole microprocessor industry thus declared that its future was in parallel computing, with a doubling of the number of processors or cores each technology generation, which occur every two years. This style of chip was labeled a multicore microprocessor. Hence, the leap to multicore is not based on a breakthrough in programming or architecture; it’s actually a retreat from the even harder task of building power-efficient, high-clock-rate, single-core chips.

Many startups tried commercializing multiple core hardware over the years. They all failed, as programmers accustomed to continuous improvements in sequential performance saw little need to explore parallelism. Convex, Encore, Floating Point Systems, INMOS, Kendall Square Research, MasPar, nCUBE, Sequent, and Thinking Machines are just the best-known members of the Dead Parallel Computer Society, whose ranks are legion. Given this sad history, there is plenty of reason for pessimism about the future of multicore. Quoting computing pioneer and Stanford President John Hennessy:

“…when we start talking about parallelism and ease of use of truly parallel computers, we’re talking about a problem that’s as hard as any that computer science has faced. … I would be panicked if I were in industry.”

Jeopardy for the IT industry means opportunity for the research community. If researchers meet the parallel challenge, the future of IT is rosy. If they don’t, it’s not. Failure could jeopardize both the IT field and the portions of the economy that depend upon rapidly improving information technology. It is also an opportunity for the leadership in IT to move from the US to wherever in the world someone invents the solution to make it easy to write efficient parallel software.

Given this current crisis, its ironic that since 2001 DARPA chose to decrease funding of academic research in computer systems research. Knowing what we know today, if we could go back in time we would have launched a Manhattan Project to bring together the best minds in applications, software architecture, programming languages and compilers, libraries, testing and correctness, operating systems, hardware architecture, and chip design to tackle this parallel challenge.

Since we don’t have time travel, there is an even greater sense of urgency to get such an effort underway. Indeed, industry has recently stepped in to fund three universities to get underway–Berkeley, Illinois, and Stanford–but its unrealistic to expect industry to fund many more. Its also clear given the urgency and importance to the industry and the nation, we can’t depend on just three academic projects to preserve the future of the US IT industry. We need the US Government to return to its historic role to bring the many more minds on these important problem. To make real progress, we would need a long-term, multi-hundred million dollar per year program.

The consequences of not funding aren’t a drop in Nobel prizes or research breakthroughs; its a decline in the US-led IT industry, a slowdown in portions of the US economy, and possibly ceding the leadership in IT to another part of the world were governments understand the potential economic impact of funding academic IT research on parallelism.

– David Patterson