Neuromorphic Platform SpiNNaker Takes Another Step Forward

By John Russell

August 21, 2018

Neuromorphic computers – intended to mimic more directly how the human brain works – hold exciting promise but for the most part remain machines in development. Most simulations of brain neural networks are run on traditional HPC resources. These latter systems, of course, can struggle with such simulations and certainly can’t approach the power efficiency achieved by the human brain (~10-20 watts). A recent comparison study suggests one neuromorphic platform – SpiNNaker – is now able to perform a type of neural network simulation typically done on an HPC system and that this advance signals its suitability for broader use in research.

“SpiNNaker can support detailed biological models of the cortex – the outer layer of the brain that receives and processes information from the senses – delivering results very similar to those from an equivalent supercomputer software simulation,” said Sacha van Albada, an author of the study and leader of the Theoretical Neuroanatomy group at the Jülich Research Centre, Germany. “The ability to run large-scale detailed neural networks quickly and at low power consumption will advance robotics research and facilitate studies on learning and brain disorders.”

An account of the work (Breakthrough in construction of computers for mimicking human brain) was recently posted on the European Human Brain Project website. In this project researchers used NEST, a neural network simulation software widely used on HPC systems. Details of the steps taken to adapt NEST to run on SpiNNaker are discussed in a paper published in Frontiers in Neuroscience.[I] The scale-up was enabled by recent developments in the SpiNNaker software stack that allow simulations to be spread across multiple boards. It’s the largest simulation yet run on SpiNNaker.

The researchers chose to model a so-called cortical microcircuit which is regarded “as unit cell of cortex repeated to cover larger areas of cortical surface and different cortical areas. The model represents the full density of connectivity in 1 mm2 of the cortical sheet by about 80,000 leaky integrate-and- fire (LIF) model neurons and 0.3 billion synapses. This is the smallest network size where a realistic number of synapses and a realistic connection probability are simultaneously achieved,” according to the paper.

There are, of course, many approaches to building neuromorphic computers, all seeking to emulate the high performance and low power consumption characteristics of human brain function. One approach is to literally etch neuron-like structures in silicon. This is done by the BrainScaleS Project. Another approach uses traditional digital parts to create neuron-like circuits. This is the tack taken by SpiNNaker which uses ARM9 cores and on-chip routers to implement a spiking neural network architecture (see SpiNNaker architecture). The SpiNNaker project is based at the University of Manchester, UK.

“[T]he present work demonstrates the usability of SpiNNaker for large-scale neural network simulations with short neurobiological time scales and compares its performance in terms of accuracy, runtime, and power consumption with that of the simulation software NEST…The result constitutes a breakthrough: as the model already represents about half of the synapses impinging on the neurons, any larger cortical model will have only a limited increase in the number of synapses per neuron and can therefore be simulated by adding hardware resources,” write the researchers.

Getting the NEST software to run on SpiNNaker was part of the challenge. The network model was originally implemented in the native simulation language interpreter (SLI) of NEST. “To allow execution also on SpiNNaker and to unify the model description across back ends, we developed an alternative implementation in the simulator-independent language PyNN. On SpiNNaker, this works in conjunction with the sPyNNaker software,” they write.

Here’s a snapshot of the test platforms:

  • HPC. NEST simulations are performed on a high-performance computing (HPC) cluster with 32 compute nodes. Each node is equipped with 2 Intel Xeon E5-2680v3 processors with a clock rate of 2.5 GHz, 128 GB RAM, 240 GB SSD local storage, and InfiniBand QDR (40 Gb/s). With 12 cores per processor and 2 hardware threads per core, the maximum number of threads per node using hyperthreading is 48. The cores can reduce and increase the clock rate (up to 3.3 GHz) in steps, depending on demand and thermal and power limits. Two Rack Power Distribution Units (PDUs) from Raritan (PX3-5530V) are used for power measurements. The HPC cluster uses the operating system CentOS 7.1 with Linux kernel 3.10.0. For memory allocation, we use jemalloc 4.1.0 in this study.
  • SpiNNaker chip

    SpiNNaker. The SpiNNaker simulations are performed using the 4.0.0 release of the software stack. The microcircuit model is simulated on a machine consisting of 6 SpiNN-5 SpiNNaker boards, using a total of 217 chips and 1934 ARM9 cores. Each board consists of 48 chips and each chip of 18 cores, resulting in a total of 288 chips and 5174 cores available for use. Of these, two cores are used on each chip for loading, retrieving results and simulation control. Of the remaining cores, only 1934 are used, as this is all that is required to simulate the number of neurons in the network with 80 neurons on each of the neuron cores.

“It is presently unclear which computer architecture is best suited to study whole-brain networks efficiently. The European Human Brain Project and Jülich Research Centre have performed extensive research to identify the best strategy for this highly complex problem. Today’s supercomputers require several minutes to simulate one second of real time, so studies on processes like learning, which take hours and days in real time are currently out of reach.” said Markus Diesmann, quoted in the HBP article, a co-author of the paper, and head of the Computational and Systems Neuroscience department at the Jülich Research Centre.

“There is a huge gap between the energy consumption of the brain and today’s supercomputers. Neuromorphic (brain-inspired) computing allows us to investigate how close we can get to the energy efficiency of the brain using electronics,” said Diesmann.

As always the devil is in the details and those are best gleaned from the paper. Simulation timing adjustments, for example, were needed. SpiNNaker achieves real-time performance for an integration time step of 1ms which “generally suffices” for applications in robotics and artificial neural networks, a “time step of 0.1ms” is typical for neuroscience applications.

The researchers are already looking ahead:

“As a consequence of the combination of required computation step size and large numbers of inputs, the simulation has to be slowed down compared to real time. In future, we will investigate the possibility of adding support for real-time performance with 0.1ms time steps. Reducing the number of neurons to be processed on each core, which we presently cannot set to fewer than 80, may contribute to faster simulation. More advanced software concepts using a synapse-centric approach open a new route for future work.”

Link to article: https://www.humanbrainproject.eu/en/follow-hbp/news/breakthrough-in-construction-of-computers-for-mimicking-human-brain/

Link to paper: https://www.frontiersin.org/articles/10.3389/fnins.2018.00291/full

[i]https://www.frontiersin.org/articles/10.3389/fnins.2018.00291/full

Performance Comparison of the Digital Neuromorphic Hardware SpiNNaker and the Neural Network Simulation Software NEST for a Full-Scale Cortical Microcircuit Model

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!

What’s New in HPC Research: Quantum Clouds, Interatomic Models, Genetic Algorithms & More

February 14, 2020

In this bimonthly feature, HPCwire highlights newly published research in the high-performance computing community and related domains. From parallel programming to exascale to quantum computing, the details are here. Read more…

By Oliver Peckham

The Massive GPU Cloudburst Experiment Plays a Smaller, More Productive Encore

February 13, 2020

In November, researchers at the San Diego Supercomputer Center (SDSC) and the IceCube Particle Astrophysics Center (WIPAC) set out to break the internet – or at least, pull off the cloud HPC equivalent. As part of thei Read more…

By Oliver Peckham

ORNL Team Develops AI-based Cancer Text Mining Tool on Summit

February 13, 2020

A group of Oak Ridge National Laboratory researchers working on the Summit supercomputer has developed a new neural network tool for fast extraction of information from cancer pathology reports to speed research and clin Read more…

By John Russell

Nature Serves up Another Challenge to Quantum Computing?

February 13, 2020

Just when you thought it was safe to assume quantum computing – though distant – would eventually succumb to clever technology, another potentially confounding factor pops up. It’s the Heisenberg Limit (HL), close Read more…

By John Russell

Researchers Enlist Three Supercomputers to Apply Deep Learning to Extreme Weather

February 12, 2020

When it comes to extreme weather, an errant forecast can have serious effects. While advance warning can give people time to prepare for the weather as it did with the polar vortex last year, the absence of accurate adva Read more…

By Oliver Peckham

AWS Solution Channel

Challenging the barriers to High Performance Computing in the Cloud

Cloud computing helps democratize High Performance Computing by placing powerful computational capabilities in the hands of more researchers, engineers, and organizations who may lack access to sufficient on-premises infrastructure. Read more…

IBM Accelerated Insights

Intelligent HPC – Keeping Hard Work at Bay(es)

Since the dawn of time, humans have looked for ways to make their lives easier. Over the centuries human ingenuity has given us inventions such as the wheel and simple machines – which help greatly with tasks that would otherwise be extremely laborious. Read more…

Eni to Retake Industry HPC Crown with Launch of HPC5

February 12, 2020

With the launch of its Dell-built HPC5 system, Italian energy company Eni regains its position atop the industrial supercomputing leaderboard. At 52-petaflops peak, HPC5 should easily crack the top ten fold of the next T Read more…

By Tiffany Trader

The Massive GPU Cloudburst Experiment Plays a Smaller, More Productive Encore

February 13, 2020

In November, researchers at the San Diego Supercomputer Center (SDSC) and the IceCube Particle Astrophysics Center (WIPAC) set out to break the internet – or Read more…

By Oliver Peckham

Eni to Retake Industry HPC Crown with Launch of HPC5

February 12, 2020

With the launch of its Dell-built HPC5 system, Italian energy company Eni regains its position atop the industrial supercomputing leaderboard. At 52-petaflops p Read more…

By Tiffany Trader

Trump Budget Proposal Again Slashes Science Spending

February 11, 2020

President Donald Trump’s FY2021 U.S. Budget, submitted to Congress this week, again slashes science spending. It’s a $4.8 trillion statement of priorities, Read more…

By John Russell

Policy: Republicans Eye Bigger Science Budgets; NSF Celebrates 70th, Names Idea Machine Winners

February 5, 2020

It’s a busy week for science policy. Yesterday, the National Science Foundation announced winners of its 2026 Idea Machine contest seeking directions for futu Read more…

By John Russell

Fujitsu A64FX Supercomputer to Be Deployed at Nagoya University This Summer

February 3, 2020

Japanese tech giant Fujitsu announced today that it will supply Nagoya University Information Technology Center with the first commercial supercomputer powered Read more…

By Tiffany Trader

Intel Stopping Nervana Development to Focus on Habana AI Chips

February 3, 2020

Just two months after acquiring Israeli AI chip start-up Habana Labs for $2 billion, Intel is stopping development of its existing Nervana neural network proces Read more…

By John Russell

Lise Supercomputer, Part of HLRN-IV, Begins Operations

January 29, 2020

The second phase of the build-out of HLRN-IV – the planned 16 peak-petaflops supercomputer serving the North-German Supercomputing Alliance (HLRN) – is unde Read more…

By Staff report

IBM Debuts IC922 Power Server for AI Inferencing and Data Management

January 28, 2020

IBM today launched a Power9-based inference server – the IC922 – that features up to six Nvidia T4 GPUs, PCIe Gen 4 and OpenCAPI connectivity, and can accom Read more…

By John Russell

Julia Programming’s Dramatic Rise in HPC and Elsewhere

January 14, 2020

Back in 2012 a paper by four computer scientists including Alan Edelman of MIT introduced Julia, A Fast Dynamic Language for Technical Computing. At the time, t Read more…

By John Russell

Cray, Fujitsu Both Bringing Fujitsu A64FX-based Supercomputers to Market in 2020

November 12, 2019

The number of top-tier HPC systems makers has shrunk due to a steady march of M&A activity, but there is increased diversity and choice of processing compon Read more…

By Tiffany Trader

SC19: IBM Changes Its HPC-AI Game Plan

November 25, 2019

It’s probably fair to say IBM is known for big bets. Summit supercomputer – a big win. Red Hat acquisition – looking like a big win. OpenPOWER and Power processors – jury’s out? At SC19, long-time IBMer Dave Turek sketched out a different kind of bet for Big Blue – a small ball strategy, if you’ll forgive the baseball analogy... Read more…

By John Russell

Intel Debuts New GPU – Ponte Vecchio – and Outlines Aspirations for oneAPI

November 17, 2019

Intel today revealed a few more details about its forthcoming Xe line of GPUs – the top SKU is named Ponte Vecchio and will be used in Aurora, the first plann Read more…

By John Russell

Dell Ramps Up HPC Testing of AMD Rome Processors

October 21, 2019

Dell Technologies is wading deeper into the AMD-based systems market with a growing evaluation program for the latest Epyc (Rome) microprocessors from AMD. In a Read more…

By John Russell

IBM Unveils Latest Achievements in AI Hardware

December 13, 2019

“The increased capabilities of contemporary AI models provide unprecedented recognition accuracy, but often at the expense of larger computational and energet Read more…

By Oliver Peckham

SC19: Welcome to Denver

November 17, 2019

A significant swath of the HPC community has come to Denver for SC19, which began today (Sunday) with a rich technical program. As is customary, the ribbon cutt Read more…

By Tiffany Trader

D-Wave’s Path to 5000 Qubits; Google’s Quantum Supremacy Claim

September 24, 2019

On the heels of IBM’s quantum news last week come two more quantum items. D-Wave Systems today announced the name of its forthcoming 5000-qubit system, Advantage (yes the name choice isn’t serendipity), at its user conference being held this week in Newport, RI. Read more…

By John Russell

Leading Solution Providers

SC 2019 Virtual Booth Video Tour

AMD
AMD
ASROCK RACK
ASROCK RACK
AWS
AWS
CEJN
CJEN
CRAY
CRAY
DDN
DDN
DELL EMC
DELL EMC
IBM
IBM
MELLANOX
MELLANOX
ONE STOP SYSTEMS
ONE STOP SYSTEMS
PANASAS
PANASAS
SIX NINES IT
SIX NINES IT
VERNE GLOBAL
VERNE GLOBAL
WEKAIO
WEKAIO

Jensen Huang’s SC19 – Fast Cars, a Strong Arm, and Aiming for the Cloud(s)

November 20, 2019

We’ve come to expect Nvidia CEO Jensen Huang’s annual SC keynote to contain stunning graphics and lively bravado (with plenty of examples) in support of GPU Read more…

By John Russell

51,000 Cloud GPUs Converge to Power Neutrino Discovery at the South Pole

November 22, 2019

At the dead center of the South Pole, thousands of sensors spanning a cubic kilometer are buried thousands of meters beneath the ice. The sensors are part of Ic Read more…

By Oliver Peckham

Fujitsu A64FX Supercomputer to Be Deployed at Nagoya University This Summer

February 3, 2020

Japanese tech giant Fujitsu announced today that it will supply Nagoya University Information Technology Center with the first commercial supercomputer powered Read more…

By Tiffany Trader

Top500: US Maintains Performance Lead; Arm Tops Green500

November 18, 2019

The 54th Top500, revealed today at SC19, is a familiar list: the U.S. Summit (ORNL) and Sierra (LLNL) machines, offering 148.6 and 94.6 petaflops respectively, Read more…

By Tiffany Trader

Azure Cloud First with AMD Epyc Rome Processors

November 6, 2019

At Ignite 2019 this week, Microsoft's Azure cloud team and AMD announced an expansion of their partnership that began in 2017 when Azure debuted Epyc-backed instances for storage workloads. The fourth-generation Azure D-series and E-series virtual machines previewed at the Rome launch in August are now generally available. Read more…

By Tiffany Trader

Intel’s New Hyderabad Design Center Targets Exascale Era Technologies

December 3, 2019

Intel's Raja Koduri was in India this week to help launch a new 300,000 square foot design and engineering center in Hyderabad, which will focus on advanced com Read more…

By Tiffany Trader

Using AI to Solve One of the Most Prevailing Problems in CFD

October 17, 2019

How can artificial intelligence (AI) and high-performance computing (HPC) solve mesh generation, one of the most commonly referenced problems in computational engineering? A new study has set out to answer this question and create an industry-first AI-mesh application... Read more…

By James Sharpe

In Memoriam: Steve Tuecke, Globus Co-founder

November 4, 2019

HPCwire is deeply saddened to report that Steve Tuecke, longtime scientist at Argonne National Lab and University of Chicago, has passed away at age 52. Tuecke Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This