The Next Step in Human Brain Simulation

By Michael Feldman

July 11, 2011

Can the human brain devise a system capable of understanding itself? That’s been something brain simulation researchers have been working toward for nearly a decade. With recent advances in supercomputing capabilities and modeling techniques, the question may soon be answered.

Understanding the fundamental workings of the brain would revolutionize neuroscience. It is estimated that about a quarter of the population in the US and Europe has some sort of brain disorder, spanning everything from anxiety attacks and mild depression to Alzheimer’s and full-blown neuroses. Brain-related health care costs currently amount to over a trillion dollars per year in the West, along with another trillion in lost productivity. To put it mildly, it is a problem that needs fixing.

The brain simulation SpiNNaker project, which recently got is first shipment of custom-built supercomputer chips, is the UK’s contribution to the effort. Far better known (and better funded) is the Blue Brain Project, headed by neuroscientist-turned-informatics-specialist Henry Markram, and run out of the École Polytechnique Fédérale in Lausanne (EPFL).

Markram is now advocating for an even more ambitious endeavor. Known as the Human Brain Project, it is a 10 year effort estimated to cost a billion euros. The goal is to build upon the knowledge accumulated under the Blue Brain work — software models, tools, supercomputing expertise — and create a multi-level simulation of the entire human brain. That will require exascale-level hardware and the software to exploit it.

At the International Supercomputing Conference in Hamburg last month, Markram described his current work and the future of virtual neuroscience. In his keynote address (available online here), he noted that the pharmaceutical industry, which funds 95 percent of the research in this area, expends its resources on a just handful of the 560 clinically classified brain disorders, in this case, the diseases that have the most attractive payoff from a drugmaker’s perspective. The other 5 percent of the funding comes from academia, which is tasked to research and develop possible treatments for the vast majority of neurological conditions.

In both cases though, the approach has been reductionist: to focus on the specific neurological structures and mechanisms that underlie a disorder. From Markram’s perspective, that strategy has led to only piecemeal progress. “The solution,” he says, “is to integrate it all… using simulations, into a unified model.”

We asked Markram to talk about the work he’s been doing on the Blue Brain Project and give us his vision of how human brain simulation will advance in the coming years.

HPCwire: Could you give us an overview of your work and what you intend to accomplish?

Henry Markram: Our mission has been to establish a radically new way approach to understanding the brain. The best way to describe it is, ICT powered biology. It is a highly integrative approach of building the brain using biological rules and data intensive computing. The brain is built on biological rules and it stands to reason you can use the same rules to build a model that generates many of the brain’s functions. The advantage of this approach is that when a function does emerge, we can actually trace a meaningful biological basis for that function.

Diseases are also likely to result where ever a rule can break and so searching for vulnerable rules provides a new strategy for predicting causes of diseases. Each step involves searching for patterns of organization in biological data (informatics), deriving rules (algorithms) and using the rules to build a new generation of models (modeling) for simulation testing (simulations). Simulating the new generation models reveals the strengths and weaknesses of the rules which we can use to refine the rules and also to find new rules that we can use to build even more accurate models.

It is a rule discovery process — a telescope into the brain which does not only depend on the hardware and software for its resolution, but also on the rules. As we build the “telescope” we can look deeper and wider into the brain, and it helps us build a better telescope: better software, better hardware, and better rules. We need constant innovations in supercomputing technologies, informatics technologies — the hardware and software. These allow us to build larger and larger brain models with more and more detail.

In 2008 we could build and simulate 10,000 neurons and 10 million synapses using a Blue Gene/L supercomputer. Today we can build models with 1 million neurons and 1 billion synapses using a Blue Gene/P supercomputer. These are not point neurons as in artificial neural networks or neuromorphic computing. They are the most detailed and accurate models of real neurons ever built. And we also now build them automatically now and we are learning how to synthesize them using basic rules.

There is a long way to go, but we have built the ICT infrastructure that now allows us to move faster. It is the first version of a platform for ICT powered biology. The models only get better and so it is a one-way track to understanding the rules that build the brain. In the process, it also provides a roadmap for supercomputing of the future. Understanding the rules also reveals computational principles which we aim to exploit in artificial neural networks and neuromorphic computing – exporting simplified circuit designs which desired functions.

We have put neuroscience on the IT highway and we will now be able to move exponentially faster. We have found dozens of new rules in the process demonstrating that this form of IT powered biology is a powerful new way of systematically integrating what we know about the brain and using ICT to chart new territory of the brain that would take experimental biology many decades to reach.

HPCwire: Who is funding the work and about how much money is involved?

Markram: We had to buy IBM’s supercomputers and this was bought not only for the Blue Brain Project, but also for many other projects. It has been funded by the universities in the area collectively. For operations, the first prototype phase till now has not been very expensive — similar to a large RO1 grant that most US scientists run on — an average of a million Swiss francs per year. To continue will cost much more and that is why we are proposing the Human Brain Project to the European Union. With a budget of around €100M per year, we can pick up speed.

HPCwire: What kind of computers are currently at your disposal? What are the current limitations of these systems in regard to the simulations?

Markram: We now have a Blue Gene/P with over 16,000 cores. Of course we are at the computing limit, we constantly need more computing power. This is perhaps the most extreme challenge for supercomputing. We will need an exascale system to simulate the human brain at a cellular level and with the capability of performing molecular resolution simulations only for zoomed areas of activity. We need to boost exascale to go beyond that.

HPCwire: What does the output of the simulation look like?

Markram: Just like experiments on real brain tissue. In other words, we can do electrical recordings, we can record the transmission between neurons or networks of neurons, we can image activity of all the neurons, we can record electrical fields generated by one neuron or all the neurons together, and so on. But, we can perform experiments that are not yet possible in the experimental lab and will not be possible for a very long time. We can record or map any parameter that we used to build the model. We can also map searched patterns of activity, etc. It is a very powerful “lab” and designed for biology-style experimentation. Like a virtual laboratory.

HPCwire: About how many lines of code are we talking about?

Markram: It is not one piece of code, it is a huge ecosystem of code that deals with the informatics, brain building, simulation, visualization, analysis, virtual lab experiments, real-time uplinks, etc. We have not counted all the lines of code, but it is long and growing.
 
HPCwire: What have you learned from the work so far?

Markram: Most importantly we established the infrastructure to do this. It is unique in the world. We have not just solved a computer science problem, but also the ultimate integration of computer science and neuroscience. We had to solve dozens of problems to get to a workable ecosystem where we can build models according to biological rules. In terms of understanding the brain, we discovered many rules that would not be possible to find experimentally.

We found general rules that now allow automated building of very accurate neurons; we found general rules that help us connect any neuron to another – the so called “connectome;” we found general rules for robustness and invariance of neural circuits, that is, we know what neural circuits are resistant to damage and what makes neural circuits that same even when the elements are different; we found general rules for emergent properties as we add columns, and many more. We also found new computing strategies that will add a new dimension to my previous discovery of liquid computing with Wolfgang Maass.

HPCwire: What is the next step for your work?

Markram: We are expanding the capability and capacity of the ICT infrastructure to allow building of a whole brain (rodent level) and to build neurons models with molecular level detail. To do this we will need to make the next step in computing power with a petascale supercomputer.

HPCwire: At what point do you think you’ll be able to simulate a complete human brain?

Markram: I always say 10 years because I believe it is technically possible in 10 years. But the clock can only start ticking once we get the proper funding to go beyond this initial stage. It cannot be done on thin air. If we get the FET Flagship grant in 2013, then by 2023-2024 we will be capable of assembling all we know to build a human brain model. If we don’t get the funding it will take decades longer.

HPCwire: Will such a simulation exhibit the same properties as the organic version? Do you think features like creativity and emotions could emerge? How about consciousness?

Markram: This is a research tool, it is not a toy to see what will happen if one builds a brain. It is not a magical model that suddenly explains to you all the secrets of the brain. It is a model that takes our knowledge to built it in the first place. We learn at each step and will probably understand most of the key principles well before we build the first model of the human brain. It is a research tool for collaborative in silico experiments and hypothesis testing.

If the model is built on biological rules and we can implement these rules accurately enough, many functions should emerge without us having to explicitly program them in. If it does not, then obviously we missed something or we could not capture the detail with sufficient accuracy. Such a “failure” is also a great success and just as important as when function does emerge, since it means that all that has gone into the model is just not enough.

Everyone argues about how much detail is needed for complex functions. Well this way, we will not have to argue. Either way we learn. You can’t lose with this approach.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

AWS Embraces FPGAs, ‘Elastic’ GPUs

December 2, 2016

A new instance type rolled out this week by Amazon Web Services is based on customizable field programmable gate arrays that promise to strike a balance between performance and cost as emerging workloads create requirements often unmet by general-purpose processors. Read more…

By George Leopold

AWS Launches Massive 100 Petabyte ‘Sneakernet’

December 1, 2016

Amazon Web Services now offers a way to move data into its cloud by the truckload. Read more…

By Tiffany Trader

Weekly Twitter Roundup (Dec. 1, 2016)

December 1, 2016

Here at HPCwire, we aim to keep the HPC community apprised of the most relevant and interesting news items that get tweeted throughout the week. Read more…

By Thomas Ayres

HPC Career Notes (Dec. 2016)

December 1, 2016

In this monthly feature, we’ll keep you up-to-date on the latest career developments for individuals in the high performance computing community. Read more…

By Thomas Ayres

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

IBM and NSF Computing Pioneer Erich Bloch Dies at 91

November 30, 2016

Erich Bloch, a computational pioneer whose competitive zeal and commercial bent helped transform the National Science Foundation while he was its director, died last Friday at age 91. Bloch was a productive force to be reckoned. During his long stint at IBM prior to joining NSF Bloch spearheaded development of the “Stretch” supercomputer and IBM’s phenomenally successful System/360. Read more…

By John Russell

Pioneering Programmers Awarded Presidential Medal of Freedom

November 30, 2016

In an awards ceremony on November 22, President Barack Obama recognized 21 recipients with the Presidential Medal of Freedom, the Nation’s highest civilian honor. Read more…

By Tiffany Trader

Seagate-led SAGE Project Delivers Update on Exascale Goals

November 29, 2016

Roughly a year and a half after its launch, the SAGE exascale storage project led by Seagate has delivered a substantive interim report – Data Storage for Extreme Scale. Read more…

By John Russell

AWS Launches Massive 100 Petabyte ‘Sneakernet’

December 1, 2016

Amazon Web Services now offers a way to move data into its cloud by the truckload. Read more…

By Tiffany Trader

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

Seagate-led SAGE Project Delivers Update on Exascale Goals

November 29, 2016

Roughly a year and a half after its launch, the SAGE exascale storage project led by Seagate has delivered a substantive interim report – Data Storage for Extreme Scale. Read more…

By John Russell

Nvidia Sees Bright Future for AI Supercomputing

November 23, 2016

Graphics chipmaker Nvidia made a strong showing at SC16 in Salt Lake City last week. Read more…

By Tiffany Trader

HPE-SGI to Tackle Exascale and Enterprise Targets

November 22, 2016

At first blush, and maybe second blush too, Hewlett Packard Enterprise’s (HPE) purchase of SGI seems like an unambiguous win-win. SGI’s advanced shared memory technology, its popular UV product line (Hanna), deep vertical market expertise, and services-led go-to-market capability all give HPE a leg up in its drive to remake itself. Bear in mind HPE came into existence just a year ago with the split of Hewlett-Packard. The computer landscape, including HPC, is shifting with still unclear consequences. One wonders who’s next on the deal block following Dell’s recent merger with EMC. Read more…

By John Russell

Intel Details AI Hardware Strategy for Post-GPU Age

November 21, 2016

Last week at SC16, Intel revealed its product roadmap for embedding its processors with key capabilities and attributes needed to take artificial intelligence (AI) to the next level. Read more…

By Alex Woodie

SC Says Farewell to Salt Lake City, See You in Denver

November 18, 2016

After an intense four-day flurry of activity (and a cold snap that brought some actual snow flurries), the SC16 show floor closed yesterday (Thursday) and the always-extensive technical program wound down today. Read more…

By Tiffany Trader

D-Wave SC16 Update: What’s Bo Ewald Saying These Days

November 18, 2016

Tucked in a back section of the SC16 exhibit hall, quantum computing pioneer D-Wave has been talking up its new 2000-qubit processor announced in September. Forget for a moment the criticism sometimes aimed at D-Wave. This small Canadian company has sold several machines including, for example, ones to Lockheed and NASA, and has worked with Google on mapping machine learning problems to quantum computing. In July Los Alamos National Laboratory took possession of a 1000-quibit D-Wave 2X system that LANL ordered a year ago around the time of SC15. Read more…

By John Russell

Why 2016 Is the Most Important Year in HPC in Over Two Decades

August 23, 2016

In 1994, two NASA employees connected 16 commodity workstations together using a standard Ethernet LAN and installed open-source message passing software that allowed their number-crunching scientific application to run on the whole “cluster” of machines as if it were a single entity. Read more…

By Vincent Natoli, Stone Ridge Technology

IBM Advances Against x86 with Power9

August 30, 2016

After offering OpenPower Summit attendees a limited preview in April, IBM is unveiling further details of its next-gen CPU, Power9, which the tech mainstay is counting on to regain market share ceded to rival Intel. Read more…

By Tiffany Trader

AWS Beats Azure to K80 General Availability

September 30, 2016

Amazon Web Services has seeded its cloud with Nvidia Tesla K80 GPUs to meet the growing demand for accelerated computing across an increasingly-diverse range of workloads. The P2 instance family is a welcome addition for compute- and data-focused users who were growing frustrated with the performance limitations of Amazon's G2 instances, which are backed by three-year-old Nvidia GRID K520 graphics cards. Read more…

By Tiffany Trader

Think Fast – Is Neuromorphic Computing Set to Leap Forward?

August 15, 2016

Steadily advancing neuromorphic computing technology has created high expectations for this fundamentally different approach to computing. Read more…

By John Russell

The Exascale Computing Project Awards $39.8M to 22 Projects

September 7, 2016

The Department of Energy’s Exascale Computing Project (ECP) hit an important milestone today with the announcement of its first round of funding, moving the nation closer to its goal of reaching capable exascale computing by 2023. Read more…

By Tiffany Trader

HPE Gobbles SGI for Larger Slice of $11B HPC Pie

August 11, 2016

Hewlett Packard Enterprise (HPE) announced today that it will acquire rival HPC server maker SGI for $7.75 per share, or about $275 million, inclusive of cash and debt. The deal ends the seven-year reprieve that kept the SGI banner flying after Rackable Systems purchased the bankrupt Silicon Graphics Inc. for $25 million in 2009 and assumed the SGI brand. Bringing SGI into its fold bolsters HPE's high-performance computing and data analytics capabilities and expands its position... Read more…

By Tiffany Trader

ARM Unveils Scalable Vector Extension for HPC at Hot Chips

August 22, 2016

ARM and Fujitsu today announced a scalable vector extension (SVE) to the ARMv8-A architecture intended to enhance ARM capabilities in HPC workloads. Fujitsu is the lead silicon partner in the effort (so far) and will use ARM with SVE technology in its post K computer, Japan’s next flagship supercomputer planned for the 2020 timeframe. This is an important incremental step for ARM, which seeks to push more aggressively into mainstream and HPC server markets. Read more…

By John Russell

IBM Debuts Power8 Chip with NVLink and Three New Systems

September 8, 2016

Not long after revealing more details about its next-gen Power9 chip due in 2017, IBM today rolled out three new Power8-based Linux servers and a new version of its Power8 chip featuring Nvidia’s NVLink interconnect. Read more…

By John Russell

Leading Solution Providers

Vectors: How the Old Became New Again in Supercomputing

September 26, 2016

Vector instructions, once a powerful performance innovation of supercomputing in the 1970s and 1980s became an obsolete technology in the 1990s. But like the mythical phoenix bird, vector instructions have arisen from the ashes. Here is the history of a technology that went from new to old then back to new. Read more…

By Lynd Stringer

US, China Vie for Supercomputing Supremacy

November 14, 2016

The 48th edition of the TOP500 list is fresh off the presses and while there is no new number one system, as previously teased by China, there are a number of notable entrants from the US and around the world and significant trends to report on. Read more…

By Tiffany Trader

Intel Launches Silicon Photonics Chip, Previews Next-Gen Phi for AI

August 18, 2016

At the Intel Developer Forum, held in San Francisco this week, Intel Senior Vice President and General Manager Diane Bryant announced the launch of Intel's Silicon Photonics product line and teased a brand-new Phi product, codenamed "Knights Mill," aimed at machine learning workloads. Read more…

By Tiffany Trader

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. Read more…

By Tiffany Trader

Beyond von Neumann, Neuromorphic Computing Steadily Advances

March 21, 2016

Neuromorphic computing – brain inspired computing – has long been a tantalizing goal. The human brain does with around 20 watts what supercomputers do with megawatts. And power consumption isn’t the only difference. Fundamentally, brains ‘think differently’ than the von Neumann architecture-based computers. While neuromorphic computing progress has been intriguing, it has still not proven very practical. Read more…

By John Russell

Dell EMC Engineers Strategy to Democratize HPC

September 29, 2016

The freshly minted Dell EMC division of Dell Technologies is on a mission to take HPC mainstream with a strategy that hinges on engineered solutions, beginning with a focus on three industry verticals: manufacturing, research and life sciences. "Unlike traditional HPC where everybody bought parts, assembled parts and ran the workloads and did iterative engineering, we want folks to focus on time to innovation and let us worry about the infrastructure," said Jim Ganthier, senior vice president, validated solutions organization at Dell EMC Converged Platforms Solution Division. Read more…

By Tiffany Trader

Container App ‘Singularity’ Eases Scientific Computing

October 20, 2016

HPC container platform Singularity is just six months out from its 1.0 release but already is making inroads across the HPC research landscape. It's in use at Lawrence Berkeley National Laboratory (LBNL), where Singularity founder Gregory Kurtzer has worked in the High Performance Computing Services (HPCS) group for 16 years. Read more…

By Tiffany Trader

Micron, Intel Prepare to Launch 3D XPoint Memory

August 16, 2016

Micron Technology used last week’s Flash Memory Summit to roll out its new line of 3D XPoint memory technology jointly developed with Intel while demonstrating the technology in solid-state drives. Micron claimed its Quantx line delivers PCI Express (PCIe) SSD performance with read latencies at less than 10 microseconds and writes at less than 20 microseconds. Read more…

By George Leopold

  • arrow
  • Click Here for More Headlines
  • arrow
Share This