Mont Blanc Forges Cluster from Smartphone Chips

By Timothy Prickett Morgan

November 22, 2013

The Mont Blanc project, an effort by a number of European supercomputing centers and vendors that seeks to create an energy-efficient supercomputer based on ARM processors and GPU coprocessors, has put together its third prototype. That is one more step on the path to an exascale system.

The third generation machine, which is being shown off at the SC13 conference in Denver this week, is by far the most elegant one that the Mont Blanc project has created thus far. This prototype supercomputer actually bears the name of the project this time around, and was preceded by the Tibidabo and Petraforca clusters, which were based on a different collection of ARM processors and GPU accelerators.

Just because this design is elegant, don’t get the wrong idea, though. The Mont Blanc machine is still a prototype, cautions Alex Ramirez, leader of the Heterogeneous Architectures Research Group at BSC who heads up the Mont Blanc project.

“In order to make this a production product, we would have to go through at least one more generation,” he says.

It stands to reason that the Mont Blanc project is waiting for the day when 64-bit ARM chips with integrated interconnects and faster GPUs are available before going into production. But for now, software can be ported to these prototypes and things can be learned about where the performance bottlenecks are and what reliability issues there might be.

The exact size of the Mont Blanc prototype cluster has not been determined yet, but Ramirez says it will have two or three racks of ARM-powered nodes. “It will be big enough to make scalability and reliability claims, but we are trying to keep the cost down on a machine that is not a production system,” he says.

Mont-Blanc-blade-carrier

The server node in the Mont Blanc system is based on the Exynos 5 system-on-chip made by Samsung, which is a dual-core ARM Cortex-A15 with an ARM Mali-T604 GPU on the die. The ARM CPU portion of the system-on-chip has about twice the performance of the quad-core Cortex-A9 processor used on the Petraforca prototype that was put together earlier this year. (There were actually two versions, but the second one is more important.) That machine used Nvidia Tesla K20 GPU coprocessors to test out how a wimpy CPU and a brawny GPU might be married. Specifically, the ARM processors, which were Tegra 3 chips running at 1.3 GHz, were put into a Mini-ITX system board with one I/O slot that was linked to a PCI-Express switch that in turn had one GPU and one ConnectX-3 40 Gb/sec InfiniBand adapter card.

The dual-core Exynos 5 chip from Samsung is used in smartphones, runs at 1.7 GHz, and has a quad-core Mali-T604 GPU that supports OpenCL 1.1. It has a dual-channel DDR3 memory controller and a USB 3.0 to 1 Gb/sec Ethernet bridge. Each Mont Blanc node is a daughter card made by Samsung that has the CPU and GPU, 4 GB of memory (1.6 GHz DDR3), a microSD slot for flash storage, and a 1 Gb/sec Ethernet network interface. All of this is crammed onto a daughter card that is 3.3 by 3.2 inches that has 6.8 gigaflops of compute on the CPU and 25.5 gigaflops of compute on the GPU for something around 10 watts of power. That works out to around 3.2 gigaflops per watt at peak theoretical performance.

The Mont Blanc system is using the Bull B505 blade server carrier and the related blade server chassis and racks to house multiple ARM server nodes. In this case, the blade carrier is fitted with a custom backplane that has a Broadcom Ethernet crossbar switch on it that links fifteen of these ARM compute nodes together. Every blade in the carrier has an Ethernet bridge chip, made by ASIX Electronics, that converts the USB port into Ethernet and then lets it hook into that Broadcom switch in the carrier.

Here is how you stack up the Mont Blanc rack:

Mont-Blanc-system

In this particular setup, says Ramirez, the location had some power density and heat density restrictions, so it was limited to four Bull blade server chassis. But the system is designed to support up to six chassis if the datacenter has enough power and cooling.

Each blade has fifteen nodes, and is a cluster in its own right. The blade delivers on the order of 485 gigaflops of compute and will burn about 200 watts. (Ramirez is estimating because he has not actually been able to do the wall power test yet because the machines just came out of the factory a few days prior to SC13.) That works out to 2.4 gigaflops per watt or so after the overhead of the network is added in.

The 7U blade chassis can hold nine carrier blades, for a total of 135 compute nodes. That works out to 4.3 teraflops in the aggregate per chassis at around 2 kilowatts of power, or 2.2 gigaflops per watt. With two 36 port 10 Gb/sec Ethernet switches to link the chassis together and 40 Gb/sec uplinks to hook into other racks, a four-chassis rack would deliver 17.2 teraflops of computing in an 8.2 kilowatt power envelope, or about 2.1 gigaflops per watt. With six blade chassis, you can get 25.8 teraflops into a rack. That is 810 chips in total per rack, by the way, with a total of 1,620 ARM cores and 3,240 Mali GPU cores.

This Mont Blanc effort will get very interesting next year, when many different ARMv8 processors, sporting 64-bit memory addressing and integrated interconnects, become available from a variety of vendors, including AppliedMicro, Calxeda, AMD, and maybe others like Samsung. Many of the components that had to be woven together in this third prototype will be unnecessary, and the thermal efficiency of the cluster will presumably rise dramatically once these features are integrated on the chips. These future ARM chips will also come with server features, such as ECC memory protection and standard I/O interfaces like PCI-Express.

“There will be enough providers that at least one of them will have exactly the kind of part you want at any given time,” says Ramirez, a bit like a kid in a candy store.

The Mont Blanc project was established in October 2011 and is a five-year effort that is coordinated by the Barcelona Supercomputer Center in Spain. British chip maker ARM Holdings, French server maker Bull, French chip maker STMicroelectronics, and British compiler tool maker Allinea are vendor participants in the Mont Blanc consortium. The University of Bristol in England, the University of Stuttgart in Germany, and the CINECA consortium of universities in Italy are academic members of the group, and the CEA, BADW-LRZ, Juelich, and BSC supercomputer centers are also members. So are a number of other institutions that promote HPC in Europe, including Inria, GENCI, and CNRS.

Mont Blanc was originally a three year project with a relatively modest budget of €14.5 million, and it has secured an additional €8.1 million in funding from the European Commission to extend it two more years. The funds are not just being used to create an exascale design, but also to create a parallel programming environment that will run on hybrid ARM-GPU machines as well as creating check pointing software to run on the clusters.

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!

AI-Focused ‘Genius’ Supercomputer Installed at KU Leuven

April 24, 2018

Hewlett Packard Enterprise has deployed a new approximately half-petaflops supercomputer, named Genius, at Flemish research university KU Leuven. The system is built to run artificial intelligence (AI) workloads and, as Read more…

By Tiffany Trader

New Exascale System for Earth Simulation Introduced

April 23, 2018

After four years of development, the Energy Exascale Earth System Model (E3SM) will be unveiled today and released to the broader scientific community this month. The E3SM project is supported by the Department of Energy Read more…

By Staff

RSC Reports 500Tflops, Hot Water Cooled System Deployed at JINR

April 18, 2018

RSC, developer of supercomputers and advanced HPC systems based in Russia, today reported deployment of “the world's first 100% ‘hot water’ liquid cooled supercomputer” at Joint Institute for Nuclear Research (JI Read more…

By Staff

HPE Extreme Performance Solutions

Hybrid HPC is Speeding Time to Insight and Revolutionizing Medicine

High performance computing (HPC) is a key driver of success in many verticals today, and health and life science industries are extensively leveraging these capabilities. Read more…

New Device Spots Quantum Particle ‘Fingerprint’

April 18, 2018

Majorana particles have been observed by university researchers employing a device consisting of layers of magnetic insulators on a superconducting material. The advance opens the door to controlling the elusive particle Read more…

By George Leopold

AI-Focused ‘Genius’ Supercomputer Installed at KU Leuven

April 24, 2018

Hewlett Packard Enterprise has deployed a new approximately half-petaflops supercomputer, named Genius, at Flemish research university KU Leuven. The system is Read more…

By Tiffany Trader

Cray Rolls Out AMD-Based CS500; More to Follow?

April 18, 2018

Cray was the latest OEM to bring AMD back into the fold with introduction today of a CS500 option based on AMD’s Epyc processor line. The move follows Cray’ Read more…

By John Russell

IBM: Software Ecosystem for OpenPOWER is Ready for Prime Time

April 16, 2018

With key pieces of the IBM/OpenPOWER versus Intel/x86 gambit settling into place – e.g., the arrival of Power9 chips and Power9-based systems, hyperscaler sup Read more…

By John Russell

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

Cloud-Readiness and Looking Beyond Application Scaling

April 11, 2018

There are two aspects to consider when determining if an application is suitable for running in the cloud. The first, which we will discuss here under the title Read more…

By Chris Downing

Transitioning from Big Data to Discovery: Data Management as a Keystone Analytics Strategy

April 9, 2018

The past 10-15 years has seen a stark rise in the density, size, and diversity of scientific data being generated in every scientific discipline in the world. Key among the sciences has been the explosion of laboratory technologies that generate large amounts of data in life-sciences and healthcare research. Large amounts of data are now being stored in very large storage name spaces, with little to no organization and a general unease about how to approach analyzing it. Read more…

By Ari Berman, BioTeam, Inc.

IBM Expands Quantum Computing Network

April 5, 2018

IBM is positioning itself as a first mover in establishing the era of commercial quantum computing. The company believes in order for quantum to work, taming qu Read more…

By Tiffany Trader

FY18 Budget & CORAL-2 – Exascale USA Continues to Move Ahead

April 2, 2018

It was not pretty. However, despite some twists and turns, the federal government’s Fiscal Year 2018 (FY18) budget is complete and ended with some very positi Read more…

By Alex R. Larzelere

Inventor Claims to Have Solved Floating Point Error Problem

January 17, 2018

"The decades-old floating point error problem has been solved," proclaims a press release from inventor Alan Jorgensen. The computer scientist has filed for and Read more…

By Tiffany Trader

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown Read more…

By Tiffany Trader

How the Cloud Is Falling Short for HPC

March 15, 2018

The last couple of years have seen cloud computing gradually build some legitimacy within the HPC world, but still the HPC industry lies far behind enterprise I Read more…

By Chris Downing

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

Chip Flaws ‘Meltdown’ and ‘Spectre’ Loom Large

January 4, 2018

The HPC and wider tech community have been abuzz this week over the discovery of critical design flaws that impact virtually all contemporary microprocessors. T Read more…

By Tiffany Trader

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate Read more…

By Rob Farber

Leading Solution Providers

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

February 22, 2018

This week Lenovo took the wraps off the ThinkSystem SD650 high-density server with third-generation direct water cooling technology developed in tandem with par Read more…

By Tiffany Trader

Fast Forward: Five HPC Predictions for 2018

December 21, 2017

What’s on your list of high (and low) lights for 2017? Volta 100’s arrival on the heels of the P100? Appearance, albeit late in the year, of IBM’s Power9? Read more…

By John Russell

AI Cloud Competition Heats Up: Google’s TPUs, Amazon Building AI Chip

February 12, 2018

Competition in the white hot AI (and public cloud) market pits Google against Amazon this week, with Google offering AI hardware on its cloud platform intended Read more…

By Doug Black

HPC and AI – Two Communities Same Future

January 25, 2018

According to Al Gara (Intel Fellow, Data Center Group), high performance computing and artificial intelligence will increasingly intertwine as we transition to Read more…

By Rob Farber

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

New Blueprint for Converging HPC, Big Data

January 18, 2018

After five annual workshops on Big Data and Extreme-Scale Computing (BDEC), a group of international HPC heavyweights including Jack Dongarra (University of Te Read more…

By John Russell

Momentum Builds for US Exascale

January 9, 2018

2018 looks to be a great year for the U.S. exascale program. The last several months of 2017 revealed a number of important developments that help put the U.S. Read more…

By Alex R. Larzelere

Google Chases Quantum Supremacy with 72-Qubit Processor

March 7, 2018

Google pulled ahead of the pack this week in the race toward "quantum supremacy," with the introduction of a new 72-qubit quantum processor called Bristlecone. Read more…

By Tiffany Trader

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