Reed's Ruminations: A Blog by Dan Reed

Digital Inclusion

As an international traveler, if you ever stood in the central Tokyo train station during rush hour, clutching a ticket in your hand and looking helplessly about, you know the feeling. If you ever stared hopelessly at a Cyrillic menu while seated in a restaurant off the beaten path in Moscow, you know the feeling. Finally, for the aging geeks among us, if you have ever tried to read someone else's APL program, you know the feeling.

It is the feeling of illiteracy and exclusion, of being unable to participate in the milieu, frustrated and dismayed, unable to communicate and understand. In the three cases above, a kindly Japanese businessman rescued me, I ordered food via hand gestures and self-deprecating smiles, and I spent some long hours reconstructing programmer intent.

Inclusion and access shape our lives. Highlighting this, a New York Times article, "Separating You and Me? 4.74 Degrees," recently reported the results of a study that used Facebook data to compute the electronic separation of Facebook participants. It was an electronic update to the oft-repeated adage that six degrees of separation connect all denizens of the planet. The results speak to the power of our electronic networks and highlight, by exception, another form of separation.

It is an equally pernicious exclusion, one crossing cultures, countries and languages. It makes no distinction between the literate and the illiterate. An economic and cultural chasm, a digital divide, separates the digitally connected from those who lack the ways or the means to join the digital community. In a knowledge economy, the separated are cut off from a plethora of services, educational materials, and business prospects.

If we are to address inequality and create opportunities for economic advancement, this must change. It is a global need, not simply a question of developed versus developing country access. The digitally disenfranchised are all around us. In some parts of the world, broadband access is an unattainable dream, beyond the economic reach of entire families. In other places, it is a non-trivial fraction of a month's income. In still others, it is either not available or its performance is inadequate. (See Broadband: Oxygen for a Digital World)

Digital inclusion matters to every society and government, for addressing inequity and access facilities better education, improved health and economic development. If we have learned anything from the history of previous economic malaises, it is that innovation and economic growth are the keys to financial recovery. Digital inclusion is one of the enablers, a catalyst for the exchange of ideas.

As I recently remarked at the closing ceremonies of the ITU Telecom World, this is not the responsibility of any one institution. The responsibility lies with all of us. No one need digitally disenfranchised.

Broadband: Oxygen for a Digital World

Much has been written about what constitutes the baseline for acceptable broadband network speeds. The U.S. National Broadband Plan includes the following recommendations:

Every household and business location in America should have access to affordable broadband service with the following characteristics:

• Actual download speeds of at least 4 Mbps and actual upload speeds of at least 1 Mbps
• An acceptable quality of service for the most common interactive applications

The FCC should review and reset this target every four years.

The latter – reviewing and updating the target regularly – is essential. What was broadband in the past is woefully inadequate today. Not long ago, a 1200-baud dial modem was an object of technological envy, and a 64 Kbps ISDN connection was beyond the reach of mere mortals. Some of us even remember acoustic couplers. Today, they are all artifacts of our Internet history.

Supercomputing and Internet History

Today's Internet traces its origins to the early ARPANET and its progeny, notably NSFNET. Although both the ARPANET and the early NSFNET were continent spanning networks, the ARPANET backbone was based on 56 Kbps links. That remained the standard backbone speed even as NSFNET was deployed to interconnect the U.S. supercomputing centers.

I was at the University of Illinois when we began the NSFNET transition to a T1 (1.5 Mbps) backbone at NCSA. The iconic image of the early NSFNET T1 backbone, shown here, was the work of my former NCSA colleagues Donna Cox and Bob Patterson. The world changed quickly after that, with deployment of a new T3 (45 Mbps) NSFNET backbone, birth of the Mosaic web browser fueling the dot.com boom and rapid deployment of dark fiber.

By 2001, Charlie Catlett and I were negotiating access to 4 10 Gbps lambdas for the NSF TeraGrid, connecting NCSA in Illinois and SDSC in California. We had initially pursued options to light ten lambdas (i.e., 100 Gbps) because we were worried that 40 Gbps might not be enough to support large-scale data sharing and high fidelity scientific visualization. We were both right and wrong. The scientific data did grow, but the scientific applications took longer to develop.

At about the same time, when I picked the name TeraGrid for the distributed grid we were building to connect the NSF supercomputing centers, Ian Foster asked me if we might later regret using the "tera" prefix in a world were supercomputing performance changed so rapidly. I replied that I thought it would last long enough, and is has, far longer than I might have expected.

Though we are now deep into the petascale computing era, we are by no means in the terabit era. Although network backbone speeds have continued rise, data volumes and user expectations have risen even more rapidly, both in scientific computing and in business and consumer web services. We are now building petabyte islands and content distribution networks (CDNs) connected by relatively slow multi-gigabit networks. I keep wondering when multi-terabit networking will be commonplace.

A Devices and Services World

Inexpensive broadband access has made possible Internet searches, cloud services and always-connected PCs, tablets and smartphones. It has transformed our society, shifted our notions of commerce, shaken governments, and brought McLuhan's global village within reach.

Thus, it is no exaggeration to say that broadband networks, wired and wireless, are the oxygen that lets this world of devices and services breathe. However, the air remains perilously thin. Billions of devices are being added to the network, data volumes are rising exponentially, and expectations for anytime, anywhere access are growing worldwide. For many, digital inclusion remains a dream, rather than a reality.

If we are to meet burgeoning demand, extend the benefits of broadband services to all of the world's population, and enable a new generation of data-rich services and experiences, we need to approach the problem of broadband deployment in new ways.

We need both top down and bottom up strategies that encourage innovation and more rapid deployment of last mile connectivity. We must rethink our approaches to spectrum allocation and access, embracing more nimble and adaptive schemes. We must expand the capabilities of our backbone networks to meet demand.

Above all, we need to remember that the definition of broadband is ever shifting. We will always want more.

One Life to Live

A few years ago, a foundation ran a billboard campaign with an image of Kermit the Frog and the caption, "Eats Flies, Dates a Pig, Hollywood Star. Live Your Dreams." Beyond being a huge fan of the Muppet Show and its sardonic humor, especially as offered by Statler and Waldorf, I have always loved this billboard because it captures an essential element of human life, the desire to make a difference, to live life with the passion of commitment. It is a feeling Thoreau captured in Walden, to the enduring delight of secondary school English teachers across North America:

I went to the woods because I wished to live deliberately, to front only the essential facts of life, and see if I could not learn what it had to teach, and not, when I came to die, discover that I had not lived.

I was reflecting on this recently as the world lost two innovators in computing. About the first, Steve Jobs, much has been written, but far less about another pioneer of computing, Dennis Ritchie.

Remembering Ritchie

UNIX and C transformed our notions of operating systems and programming, seeding a cornucopia of software tools and technologies. I still have my dog-eared copy of the 1978 Bell Systems Technical Journal (BSTJ), which was devoted to the "UNIX Timesharing System."

I was a graduate student then, and it brought my first exposure to UNIX on a VAX 11/780 at Purdue. We ran VMS part of the time and UNIX the rest, largely because VMS had a decent FORTRAN compiler. The numerical analysts among us used FORTRAN, but for the rest, it was UNIX and C. It was a heady time, when new tools and approaches were transforming academic computing research from a largely theoretical discipline to an experimental science. I created a compiler for John Backus' FP language using lex and yacc on that VAX, and I wrote a Ph.D. dissertation using troff.

As da Vinci supposedly remarked, "Simplicity is the ultimate sophistication." UNIX was elegant in its simplicity and functionality. It and the C language inspired multiple generations of hackers (and I use that word in its original, pure sense) to create so many things. It is not exaggeration to say that one can date operating systems as pre-UNIX and post-UNIX.

Richie's passing was not noted with great fanfare, but he made a difference. All of us in computing honor that.

Meditations on Dreams

In between the endless work deadlines, the email deluge and the frenzied travel, take a deep breath and ask yourself what matters and what you are doing. The answers may surprise you, particularly as mortality seems more than a tale told by the wise and aged to the young and uncertain. Those are the essential facts Thoreau described.

Throughout my life, I have been able to live many of my dreams. Far too many people are not so fortunate. (For the record, eating flies, dating a pig and being a Hollywood star have not been among them.) I have a few dreams left, both in computing and in life, and I suspect you do too. In my case, there is a book or two trying to escape via my fingers. (See Eudora, You Got the Love?)

Seize the opportunity. Live your dreams. Make a difference. It is all that any of us can hope to do.

Surrounded By Opportunities

Perhaps the closest I have approached the feeling of intellectual omnipotence (and it has not been often) was when I was a graduate student, teaching undergraduate FORTRAN programming for science and engineering students. Those were the days of punched cards, batch processing and line printer output. It was a time when dinosaurs roamed the earth, my slide rule was still a fond memory, and we were computing on massive machines with less performance than my smartphone has today. (Ignore that part about the dinosaurs, as it was a wee bit earlier.)

During my office hours, students would troop through for help with their programming assignments, bringing program printouts. These printouts began with a "day file" showing the timeline of compilation and execution steps (JCL steps on IBM S/360), followed by the program and then any output. After having seen a few students, you realize that elementary programming errors have just a few equivalence classes, often identifiable from the day file alone. I took great pride in listening to the student description of the problem, predicting the root cause and then immediately locating it on the printout. The student was inevitably amazed. Yes, it was a cheap parlor trick, but as a graduate student, you take gratification where you can find it.

All of this reminds me that sequential programming remains difficult and parallel programming even more difficult, despite all our efforts to tame the unruly beast with syntactic sugar, specification and scripting languages, libraries and tools. I am no expert in parallel programming language design, nor am I a cognitive psychologist, but like many of my readers, I have pulled a few all-nighters writing code. Perhaps that at least qualifies me to have an opinion.

In a world of parallel programming, multicore architectures, dark silicon, and rising software complexity, we face some difficult choices. It's time to learn from the past.

Fading Abstractions

We have been fortunate to date. Although sequential programming at scale is intellectually challenging, we have been riding the wave of ever-increasing processor performance, made possible by semiconductor advances. In turn, these were based on an abstraction – the Mead-Conway design rules –that largely separated device physics from microprocessor architecture. Finally, the von Neumann abstraction has also served us well, allowing decades of software development atop an easily understood model of sequential instruction execution.

Our run of good luck is over. Put another way, we are surrounded by opportunities! Parallelism is now the norm for almost all software developers, not just those of us in high-performance computing. More perniciously, heterogeneous parallelism is here, with disparate cores, accelerators and functional units. To manage dark silicon and exploit continuing transistor density increases, this trend will only accelerate, with a dizzying array of heterogeneous chips and devices challenging code portability and performance tuning. Finally and most worrisome, our device physics abstractions are breaking down, with device physics affecting architecture. We face real silicon reliability, process variation and energy challenges, and near threshold voltage computations emerging.

Holistic Collaboration

The abstractions of device physics, processor architecture and programming models naturally led to a corresponding intellectual specialization. Consequently, those working in materials science and device physics have little in common with those designing software tools. I believe that must change if we are to address our challenges.

We need new, integrated design methodologies and rich collaborations that consider end-to-end design and capability. In many ways, this is a return to the past, necessitated by the desire for continuing increases in performance, mediated by the desire for reliability, scalability, programmability and economic feasibility. It will not be easy, but it is a way forward.

Why We Compute

N.B. I also write for the Communications of the ACM (CACM). The following essay recently appeared on the CACM blog.

Why do we, as researchers and practitioners, have this deep and abiding love of computing? Why do we compute? Superficially, the question seems as innocuous as asking why the sky is blue or the grass is green. However, like both of those childhood questions, the simplicity belies the subtlety beneath. Just ask someone about Raleigh scattering or the quantum efficiency of photosynthesis if you doubt that simple questions can unearth complexity.

At its most basic, computing is simply automated symbol manipulation. Indeed, the abstract Turing machine does nothing more than manipulates symbols on a strip of tape using a table of rules. More deceptively, the rules seem simpler than some board games. Though vacuously true, the description misses the point that symbol manipulation under those rules captures what we now call the Church-Turing thesis.

However, as deep and as beautiful as the notion of computability really is, I doubt that is the only reason most of us are so endlessly fascinated by this malleable thing we call computing. Rather, I suspect it is a deeper, more primal yearning, one that underlies all of science and engineering and that unites us in a common cause. It is the insatiable desire to know and understand.

Lessons from Astronomy

When I recently I stood atop Mauna Kea, looking at the array of telescopes perched there, I was again struck by our innate curiosity. Operated by a diverse array of international partnerships and built on Mauna Kea at great expense, they are there because we care about some fundamental questions. What is the evolutionary history and future of the universe? What are dark matter and dark energy? Why is there anything at all?

Answers to these questions are not likely to address our current economic woes, improve health care or address our environmental challenges. We care about the answers, nevertheless.

As I pondered the gloaming sky, my thoughts turned to Edwin Hubble, who first showed that some of those faint smudges in the sky were "island universes" – galaxies like our own. The universe was a far bigger place than we had heretofore imagined. As Hubble observed about this age-old quest to understand:

From our home on the Earth, we look out into the distances and strive to imagine the sort of world into which we are born. Today we have reached far out into Space. Our immediate neighborhood we know rather intimately. But with increasing distance our knowledge fades, and fades rapidly, until at the last dim horizon we search among ghostly errors of observations for landmarks that are scarcely more substantial. The search will continue. The urge is older than history. It is not satisfied and it will not be suppressed.

Hubble's comment was about the observational difficulties of distance estimation and the challenges associated with identifying standard candles. However, it could just as easily have been a meditation on computing, for we are driven by our own insatiable desires for better algorithms, more flexible and reliable software, new sensors and data analytics tools, and by ever larger and more faster computers.

Computing the Future

Why do we compute? I suspect it is for at least two, related reasons, neither relating to publication counts, tenure, wealth or fame. The first is the ability to give life to the algorithmic instantiation of an idea, to see it dance and move across our displays and devices. We have all felt the exhilaration when the idea takes shape in code, then begins to execute, sometimes surprising us in its unexpected behavior and complexity. Computing's analog of deus ex machina brings psychic satisfaction.

The second reason is that computing is an intellectual amplifier, extending our nominal reach and abilities. I discussed the power of computing to enable and enhance exploration in another CACM blog. (See Intellectual Amplification via Computing.) It is why those of us in computational science continually seek better algorithms and faster computer systems. From terascale to petascale and the global race to exascale, it is a quest for greater fidelity, higher resolution and finer time scales. The same deep yearning drives astronomers to seek higher resolution detectors and larger telescope apertures. We are all chasing searching the ghostly signals for landmarks.

It is our ability to apply our ideas and their embodiment in code to a dizzying array of problems, from the prosaic to the profound, that attracts and compels us. It is why we compute.

Hubble was right. We compute because we want to know and understand. The urge is deep and unsatisfied. It cannot be denied.