GPGPUs Make Headway in Bioscience

By Michael Feldman

June 25, 2008

Few user organizations have had more hands-on experience with accelerators than the National Cancer Institute’s Advanced Biomedical Computing Center (ABCC). We asked Jack Collins, manager of the ABCC’s Scientific Computation and Program Development group, for his take on accelerator appropriateness.

HPCwire: You and others at your site have experimented heavily with accelerators over the years, first Cray bit matrix multipliers, then FPGAs and now GPUs. Why?

Jack Collins: As the sizes of the scientific problems that we encounter scale, so must our solutions to computational demands. For instance, next-gen sequencing is generating terabytes of information and we need to analyze it quickly because whole farms of these machines are being deployed. Also, imaging is now being fully integrated into the workflow and not being treated as a separate area. From the technology side, price/performance is a big driver. Price includes the total cost of ownership: power, cooling, programming, etc. And when you look at new technologies, such as the Tesla card, that offer one teraflop performance you can get a lot of bang for the buck.

HPCwire: What applications are you trying to accelerate? Can you talk about them in some detail?

Collins: There are several applications. The most straightforward for GPGPU is molecular dynamics and simulation. There is a lot of computation in the kernel and it maps very well to the hardware. An example would be NAMD. It was ported to the GPGPU by University of Illinois folks and they got a factor of about 200x speedup. We have other codes that have a similar kernel so we expect similar results. Small molecule-protein docking is another area where we are using the GPGPU. Right now we’re at about 10x over the latest Xeon processor, and we should see another 2 to 4x with a couple of more tweaks.

We’re also looking at imaging applications where the processing and analysis is taking too long. Analyzing 3D images using a GPGPU for the computation and another to display the results is something we’re very interested in. These applications map very well to the architecture. We’re also exploring bioinformatics applications, but the really great thing about the GPGPU and CUDA right now is that post-docs and universities are porting codes and putting them back into the public domain at an incredible rate. This means that the community effort can be used to leverage standard codes without a large investment. Everyone has a GPU, and CUDA can be gotten by just hitting the download button in your browser.

HPCwire: What have you learned about using accelerators?

Collins: In general, you must realize that you’re taking a risk. Things generally sound better than they actually perform. Basically, I now ask about the programming model before I even care about how the hardware works. If there is no reasonable way to program the system, even if it’s buggy and a bit clunky, then pass unless you have resources to burn on a project that is high risk. Another important thing is the market being targeted. If the market isn’t big enough to support the company, then the company and product may disappear whether it works or not.

HPCwire: Why are you working with GPUs today?

Collins: GPUs have several advantages over other accelerators right now. First, they don’t cost that much. Second, everyone has access to both the hardware and the programming tools. Once it’s in the hands of that many people, the number of applications and tools will simply take off. Third, and quite importantly, the performance is truly staggering. And finally, the programming model is being developed hand-in-hand, at least at NVIDIA, with the hardware development, with the goal of making it accessible to general programmers and not just specialists.

HPCwire: Have you abandoned FPGAs?

Collins: No. But our efforts have been scaled back significantly.

HPCwire: GPUs generally lack 64-bit precision and error correction capability. Are those important for any of your applications?

Collins: For many of our applications we can live with these limitations, especially when we’re doing some Monte Carlo or genetic algorithm runs that are averaged over a large number of simulations. However, I think that the new NVIDIA products are addressing these limitations.

HPCwire: What results have you gotten from using GPUs so far?

Collins: We’ve gotten some nice speedups on molecular docking, as I said earlier. Talking to others, preliminary numbers look very good on the other codes I described as well. The results are good enough to change the way we approach problems from a business workflow perspective.

HPCwire: How difficult are GPUs to program and work with compared with other accelerators you’ve tried?

Collins: Compared to earlier accelerators where you needed special libraries that may have severe limitations, or to FPGAs where one needed to understand the basic hardware, the CUDA programming model is relatively straightforward. In my mind it’s more like OpenMP or UPC. You may have to restructure your code or algorithm to get good performance, but you can still recognize the programming language when you’re done.

HPCwire: What are you hoping for from GPUs?

Collins: For problems that map well to the GPU, it can dramatically change the workflow of our scientists. On the desktop it can bring a lot of analyses into the “doable” or “interactive” realm, and that can really change the way we attack a problem. In the computing center, adding nodes of GPU that can accelerate an application by 100x can free up that many cores on my compute servers and reduce my power and cooling requirements to keep up with demand. Adding a GPU instead of another 100 cores is much easier if the software supports it. When the next generation of GPU comes out, I can simply replace it. And finally, at home I have a supercomputer in a box. At one teraflop for a new Tesla card, I can do a lot on my home computer now.

HPCwire: What company or companies are you working with, and what kind of products do they have?

Collins: For GPGPUs I’m primarily working with NVIDIA, and I’m focused on the Tesla card that they’ve just announced. We’re also working with Silicon Informatics to help us port code to GPUs in the drug design and discovery area.

HPCwire: What’s the collaborative model you’re using to work with them?

Collins: They’re providing training, advanced access to hardware, and actually listening to us about what is important for our problems. We’ve worked through direct communication as well as bringing some of our vendors together with NVIDIA to build a better product before it gets to us.

HPCwire: What advice do you have for other HPC users who are considering adding accelerators to their computing mix?

Collins: See if their problem maps to the accelerator they are considering. Determine what speedup is necessary for their applications to make a good business justification for porting to the new hardware. Are they looking for 2x, 10x, 100x? Is that goal realistic? And check out the programming model that is necessary to take advantage of the accelerator. If it takes six months to compute the problem on today’s hardware or six hours on an accelerator after ten years of coding, the answer becomes obvious when you look at the total time to solution. And we’re really interested in answering the question, right?

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!

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 planned U.S. exascale computer. Intel also provided a glimpse of Read more…

By John Russell

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 cutting for the Expo Hall opening is Monday at 6:45pm, with the Read more…

By Tiffany Trader

SC19’s HPC Impact Showcase Chair: AI + HPC a ‘Speed Train’

November 16, 2019

This year’s chair of the HPC Impact Showcase at the SC19 conference in Denver is Lori Diachin, who has spent her career at the spearhead of HPC. Currently deputy director for the U.S. Department of Energy’s (DOE) Read more…

By Doug Black

Microsoft Azure Adds Graphcore’s IPU

November 15, 2019

Graphcore, the U.K. AI chip developer, is expanding collaboration with Microsoft to offer its intelligent processing units on the Azure cloud, making Microsoft the first large public cloud vendor to offer the IPU designe Read more…

By George Leopold

At SC19: What Is UrgentHPC and Why Is It Needed?

November 14, 2019

The UrgentHPC workshop, taking place Sunday (Nov. 17) at SC19, is focused on using HPC and real-time data for urgent decision making in response to disasters such as wildfires, flooding, health emergencies, and accidents. We chat with organizer Nick Brown, research fellow at EPCC, University of Edinburgh, to learn more. Read more…

By Tiffany Trader

AWS Solution Channel

Making High Performance Computing Affordable and Accessible for Small and Medium Businesses with HPC on AWS

High performance computing (HPC) brings a powerful set of tools to a broad range of industries, helping to drive innovation and boost revenue in finance, genomics, oil and gas extraction, and other fields. Read more…

IBM Accelerated Insights

Data Management – The Key to a Successful AI Project

 

Five characteristics of an awesome AI data infrastructure

[Attend the IBM LSF & HPC User Group Meeting at SC19 in Denver on November 19!]

AI is powered by data

While neural networks seem to get all the glory, data is the unsung hero of AI projects – data lies at the heart of everything from model training to tuning to selection to validation. Read more…

China’s Tencent Server Design Will Use AMD Rome

November 13, 2019

Tencent, the Chinese cloud giant, said it would use AMD’s newest Epyc processor in its internally-designed server. The design win adds further momentum to AMD’s bid to erode rival Intel Corp.’s dominance of the glo Read more…

By George Leopold

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

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

SC19’s HPC Impact Showcase Chair: AI + HPC a ‘Speed Train’

November 16, 2019

This year’s chair of the HPC Impact Showcase at the SC19 conference in Denver is Lori Diachin, who has spent her career at the spearhead of HPC. Currently Read more…

By Doug Black

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

Intel AI Summit: New ‘Keem Bay’ Edge VPU, AI Product Roadmap

November 12, 2019

At its AI Summit today in San Francisco, Intel touted a raft of AI training and inference hardware for deployments ranging from cloud to edge and designed to support organizations at various points of their AI journeys. The company revealed its Movidius Myriad Vision Processing Unit (VPU)... Read more…

By Doug Black

IBM Adds Support for Ion Trap Quantum Technology to Qiskit

November 11, 2019

After years of percolating in the shadow of quantum computing research based on superconducting semiconductors – think IBM, Rigetti, Google, and D-Wave (quant Read more…

By John Russell

Tackling HPC’s Memory and I/O Bottlenecks with On-Node, Non-Volatile RAM

November 8, 2019

On-node, non-volatile memory (NVRAM) is a game-changing technology that can remove many I/O and memory bottlenecks and provide a key enabler for exascale. That’s the conclusion drawn by the scientists and researchers of Europe’s NEXTGenIO project, an initiative funded by the European Commission’s Horizon 2020 program to explore this new... Read more…

By Jan Rowell

MLPerf Releases First Inference Benchmark Results; Nvidia Touts its Showing

November 6, 2019

MLPerf.org, the young AI-benchmarking consortium, today issued the first round of results for its inference test suite. Among organizations with submissions wer Read more…

By John Russell

Supercomputer-Powered AI Tackles a Key Fusion Energy Challenge

August 7, 2019

Fusion energy is the Holy Grail of the energy world: low-radioactivity, low-waste, zero-carbon, high-output nuclear power that can run on hydrogen or lithium. T Read more…

By Oliver Peckham

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

Cray Wins NNSA-Livermore ‘El Capitan’ Exascale Contract

August 13, 2019

Cray has won the bid to build the first exascale supercomputer for the National Nuclear Security Administration (NNSA) and Lawrence Livermore National Laborator Read more…

By Tiffany Trader

DARPA Looks to Propel Parallelism

September 4, 2019

As Moore’s law runs out of steam, new programming approaches are being pursued with the goal of greater hardware performance with less coding. The Defense Advanced Projects Research Agency is launching a new programming effort aimed at leveraging the benefits of massive distributed parallelism with less sweat. Read more…

By George Leopold

AMD Launches Epyc Rome, First 7nm CPU

August 8, 2019

From a gala event at the Palace of Fine Arts in San Francisco yesterday (Aug. 7), AMD launched its second-generation Epyc Rome x86 chips, based on its 7nm proce 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

Ayar Labs to Demo Photonics Chiplet in FPGA Package at Hot Chips

August 19, 2019

Silicon startup Ayar Labs continues to gain momentum with its DARPA-backed optical chiplet technology that puts advanced electronics and optics on the same chip Read more…

By Tiffany Trader

Crystal Ball Gazing: IBM’s Vision for the Future of Computing

October 14, 2019

Dario Gil, IBM’s relatively new director of research, painted a intriguing portrait of the future of computing along with a rough idea of how IBM thinks we’ Read more…

By John Russell

Leading Solution Providers

ISC 2019 Virtual Booth Video Tour

CRAY
CRAY
DDN
DDN
DELL EMC
DELL EMC
GOOGLE
GOOGLE
ONE STOP SYSTEMS
ONE STOP SYSTEMS
PANASAS
PANASAS
VERNE GLOBAL
VERNE GLOBAL

Intel Confirms Retreat on Omni-Path

August 1, 2019

Intel Corp.’s plans to make a big splash in the network fabric market for linking HPC and other workloads has apparently belly-flopped. The chipmaker confirmed to us the outlines of an earlier report by the website CRN that it has jettisoned plans for a second-generation version of its Omni-Path interconnect... Read more…

By Staff report

Kubernetes, Containers and HPC

September 19, 2019

Software containers and Kubernetes are important tools for building, deploying, running and managing modern enterprise applications at scale and delivering enterprise software faster and more reliably to the end user — while using resources more efficiently and reducing costs. Read more…

By Daniel Gruber, Burak Yenier and Wolfgang Gentzsch, UberCloud

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

Rise of NIH’s Biowulf Mirrors the Rise of Computational Biology

July 29, 2019

The story of NIH’s supercomputer Biowulf is fascinating, important, and in many ways representative of the transformation of life sciences and biomedical res Read more…

By John Russell

Xilinx vs. Intel: FPGA Market Leaders Launch Server Accelerator Cards

August 6, 2019

The two FPGA market leaders, Intel and Xilinx, both announced new accelerator cards this week designed to handle specialized, compute-intensive workloads and un Read more…

By Doug Black

When Dense Matrix Representations Beat Sparse

September 9, 2019

In our world filled with unintended consequences, it turns out that saving memory space to help deal with GPU limitations, knowing it introduces performance pen Read more…

By James Reinders

With the Help of HPC, Astronomers Prepare to Deflect a Real Asteroid

September 26, 2019

For years, NASA has been running simulations of asteroid impacts to understand the risks (and likelihoods) of asteroids colliding with Earth. Now, NASA and the European Space Agency (ESA) are preparing for the next, crucial step in planetary defense against asteroid impacts: physically deflecting a real asteroid. Read more…

By Oliver Peckham

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

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