Think Fast: IBM Talks Acceleration in HPC and the Enterprise

By John Russell

November 16, 2015

At SC15 today, IBM provided a glimpse of its broadening vision for accelerator-assisted computing with announcements around Watson, a strategic alliance with FPGA specialist Xilinx, an expanded developer outreach via the SuperVessel program, and new efforts to accelerate the datacenter and a wide variety of applications used in both HPC and the enterprise.

“Accelerators have come to play a dominant role in HPC and we believe the notion of an accelerated datacenter is beginning to creep into the enterprise and will become a dominant factor,” Sumit Gupta, vice president, HPC and OpenPOWER operations at IBM told HPCwire. The IBM vision encompasses roles for both GPU- and FPGA- accelerated systems integrated with OpenPOWER architecture and taking advantage of CAPI interface. Gupta outlined what he called an ambitious three-pronged effort to accelerate computing, storage and networking.

GPUs, of course, have proven very powerful in HPC. More than 100 of the TOP500 machines from the list announced this morning rely on GPU acceleration, accounting for a total 143 petaflops – more than one-third of the list’s total FLOPS. NVIDIA Tesla GPU-based supercomputers comprise 70 of these systems – including 23 of the 24 new systems on the list.

Accelerators.TOP500.SC15As shown here the mix of accelerators powering the TOP500 is growing (source: Top500). With Moore’s Law topping out, IBM is betting accelerators, both GPUs and FPGAs, will become pivotal to improving performance not only for traditional HPC applications, but also for big data and data analytics challenges.

As part of the barrage of accelerator news, IBM noted for the first time that Watson, IBM’s “cognitive computing” platform, has been accelerated with NVIDIA Tesla K80 GPUs coupled to Watson’s POWER-based architecture. According to IBM, Watson’s retrieve and rank API capability is now 1.7x of its normal speed and Watson’s processing power up to 10x its prior performance according.

Other important bullet points include:

  • Newest OpenPOWER Platinum member Xilinx and IBM have a multi-year strategic collaboration to develop and market a series of data center and network function virtualization (NFV) solutions with systems, software, and management components around Xilinx FPGA accelerators. Solutions will focus on emerging workloads including high performance computing, cognitive computing, machine learning, genomics and big data analytics.
  • IBM reiterated Mellanox support of CAPI with its earlier release of the world’s first smart network switch, the Switch-IB 2, capable of delivering clients 10x system performance improvement. NEC announced availability of its ExpEther Technology that is also suited for POWER architecture-based systems, along with plans to leverage IBM’s CAPI technology in 2016.
  • OpenPOWER members, E4 Computer Engineering and Penguin Computing, announced new systems based on the OpenPOWER architecture and incorporating POWER8 and NVIDIA Tesla GPU accelerators.
  • IBM has ported a series of key IBM Internet of Things, Spark, Big Data and Cognitive Era applications to take advantage of the POWER architecture with accelerators.

As part of the IBM and Xilinx strategic collaboration, IBM Systems Group developers will create solution stacks for POWER-based servers, storage and middleware systems with Xilinx FPGA accelerators for data center architectures such as OpenStack, Docker, and Spark. IBM will also develop and qualify Xilinx accelerator boards into IBM Power Systems servers. Xilinx is developing and will release POWER-based versions of its leading software defined SDAccel Development Environment and libraries for the OpenPOWER developer community.

IBM suggests that as heterogeneous workloads have become increasingly prevalent, data centers are turning to application accelerators to keep up with the demands for throughput and latency at low power. Xilinx FPGAs, reports IBM, can deliver the power efficiency that makes accelerators practical to deploy throughout the data center.

SumitGupta_120x168Gupta couldn’t resist taking a swipe at Intel. “The difference between our platform and the x86 platform is that we actually partner with Xilinx and NVIDIA to build tightly integrated interfaces like CAPI and NVlink and put our investments together to come to market with an open collaborative solutions. This is in stark contrast to [the] competing solution which is completely closed, proprietary, and all designed from one vendor.”

The war of words aside, it will be interesting to watch the competing approaches play out. IBM and the OpenPOWER favor a multiple discrete component approach that is optimized and tightly glued together through collaborative design. Intel is betting that bringing these functions together under one roof, and mostly in silicon, will end up delivering higher performance. No doubt both have advantages. Stay tuned.

Commenting on the expanding role of FPGAs and GPUs, Gupta said IBM sees the two technologies as complementary. Some workloads such as deep learning and model training are currently best suited for GPUs, he said. Conversely, once the model is set and objects identified, FPGAs can handle those workloads well.

He added IBM is seeing more use of FPGAs in a variety of workloads – genomics is one – and network processing is another. The latter permits use of a standard server with FPGA-based specialization rather than the use of distinct dedicated boxes for differing network applications such as security or packet processing. Network virtualization will significantly benefit from FPGAs, he said.

Currently, IBM is working on accelerating a wide range of applications. “We have an accelerated storage solution [in which] we connect our flash using CAPI to the POWER system [which] is very useful to accelerate NoSQL database applications, which are basically analytics,” Gupta said. He pointed to Apache Spark and NoSQL databases Redis and Neo4j as examples of application acceleration being undertaken by IBM.

Obviously, getting OpenPOWER systems with accelerators into the hands of developers is a necessary part of IBM’s strategy. To that end, IBM reported expanding GPU services on SuperVessel, the global cloud-based OpenPOWER ecosystem resource launched in June and initially based only in China. SuperVessel now provides GPU-accelerated computing as-a-service capabilities, giving users access to high-performance NVIDIA Tesla GPUs to enable Caffe, Torch and Theano deep-learning frameworks to instantaneously launch from the SuperVessel cloud.

“We are also announcing a new SuperVessel system that will serve North America and Europe. This will dramatically increase developer access,” said Gupta. As part of the expansion, Xilinx and IBM have developed a new FPGA accelerator service on SuperVessel that makes coherent reconfigurable accelerators available to developers via the cloud. By enabling high-level language programming like C, C++ and OpenCL, Xilinx and IBM are attempting to dramatically expand how users leverage FPGAs in the cloud for innovation on applications like machine learning, big data analytics and HPC.

IBM is also adding developer resources at the University of Texas and Oregon State University aimed at the academic research community, “but which anyone can apply for” said Gupta. He noted IBM has already developed proof-point case studies such as one based on work at Baylor College, which used accelerators and a Power system for genomics applications.

  • The Baylor team, led by geneticist and computer scientist Erez Lieberman Aiden, developed a new procedure to modify how a human genome is arranged in three dimensions in the nucleus of a cell. The work was done using a Power System accelerated with NVIDIA Tesla GPUs and Mellanox network infrastructure “to build a 3-D map of the human genome and model the reaction of the genome to this surgical procedure, without disturbing the surrounding DNA.”
  • At OSU, the Open Source Lab (OSUOSL) has increased the footprint of POWER8-based systems in their existing OpenStack cluster with additional compute and memory capacity. The expansion significantly increases the number of distinct users OSUOSL can support for research and development on OpenPOWER/OpenStack infrastructures.

IBM logoIBM offered another bit of evidence for OpenPOWER Foundation’s gathering momentum: new member Texas Advanced Computing Center (TACC) at University of Texas at Austin, and IBM announced a POWER8 accelerated computing cluster to be made available to academic researchers and developers. The new cluster is currently running successfully in an early user mode, and will begin accepting requests for access this week.

On balance, today’s IBM news was all about the rise of accelerator-assisted computing and IBM’s embrace of it, including its steady march into the enterprise.

“There is a need for systems that provide greater speed to insight — for data and analytics workloads to help businesses and organization make sense of the data, to outthink competitors as we usher in a new era of Cognitive Computing,” said Brad McCredie, IBM Fellow and OpenPOWER Foundation President. “IBM and our more than 160 partners in the OpenPOWER Foundation are on the forefront driving the changes necessary for innovation at all levels of the technology stack, including the development the industry’s first open, high-speed interconnects between processors and accelerators.”

Subscribe to HPCwire's Weekly Update!

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

Empowering High-Performance Computing for Artificial Intelligence

April 19, 2024

Artificial intelligence (AI) presents some of the most challenging demands in information technology, especially concerning computing power and data movement. As a result of these challenges, high-performance computing Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that have occurred about once a decade. With this in mind, the ISC Read more…

2024 Winter Classic: Texas Two Step

April 18, 2024

Texas Tech University. Their middle name is ‘tech’, so it’s no surprise that they’ve been fielding not one, but two teams in the last three Winter Classic cluster competitions. Their teams, dubbed Matador and Red Read more…

2024 Winter Classic: The Return of Team Fayetteville

April 18, 2024

Hailing from Fayetteville, NC, Fayetteville State University stayed under the radar in their first Winter Classic competition in 2022. Solid students for sure, but not a lot of HPC experience. All good. They didn’t Read more…

Software Specialist Horizon Quantum to Build First-of-a-Kind Hardware Testbed

April 18, 2024

Horizon Quantum Computing, a Singapore-based quantum software start-up, announced today it would build its own testbed of quantum computers, starting with use of Rigetti’s Novera 9-qubit QPU. The approach by a quantum Read more…

2024 Winter Classic: Meet Team Morehouse

April 17, 2024

Morehouse College? The university is well-known for their long list of illustrious graduates, the rigor of their academics, and the quality of the instruction. They were one of the first schools to sign up for the Winter Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that ha Read more…

Software Specialist Horizon Quantum to Build First-of-a-Kind Hardware Testbed

April 18, 2024

Horizon Quantum Computing, a Singapore-based quantum software start-up, announced today it would build its own testbed of quantum computers, starting with use o Read more…

MLCommons Launches New AI Safety Benchmark Initiative

April 16, 2024

MLCommons, organizer of the popular MLPerf benchmarking exercises (training and inference), is starting a new effort to benchmark AI Safety, one of the most pre Read more…

Exciting Updates From Stanford HAI’s Seventh Annual AI Index Report

April 15, 2024

As the AI revolution marches on, it is vital to continually reassess how this technology is reshaping our world. To that end, researchers at Stanford’s Instit Read more…

Intel’s Vision Advantage: Chips Are Available Off-the-Shelf

April 11, 2024

The chip market is facing a crisis: chip development is now concentrated in the hands of the few. A confluence of events this week reminded us how few chips Read more…

The VC View: Quantonation’s Deep Dive into Funding Quantum Start-ups

April 11, 2024

Yesterday Quantonation — which promotes itself as a one-of-a-kind venture capital (VC) company specializing in quantum science and deep physics  — announce Read more…

Nvidia’s GTC Is the New Intel IDF

April 9, 2024

After many years, Nvidia's GPU Technology Conference (GTC) was back in person and has become the conference for those who care about semiconductors and AI. I Read more…

Google Announces Homegrown ARM-based CPUs 

April 9, 2024

Google sprang a surprise at the ongoing Google Next Cloud conference by introducing its own ARM-based CPU called Axion, which will be offered to customers in it Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Leading Solution Providers

Contributors

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Eyes on the Quantum Prize – D-Wave Says its Time is Now

January 30, 2024

Early quantum computing pioneer D-Wave again asserted – that at least for D-Wave – the commercial quantum era has begun. Speaking at its first in-person Ana Read more…

GenAI Having Major Impact on Data Culture, Survey Says

February 21, 2024

While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to Read more…

The GenAI Datacenter Squeeze Is Here

February 1, 2024

The immediate effect of the GenAI GPU Squeeze was to reduce availability, either direct purchase or cloud access, increase cost, and push demand through the roof. A secondary issue has been developing over the last several years. Even though your organization secured several racks... Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire