The Future Looks Bright for Teraflop Computing
Wouldn’t it be great to have a teraflop of computing power sitting in your lab, desktop workstation, or remote instrument server? Talk about simplifying workflows, eliminating competition for HPC resources, and allowing more scientists and technicians to get more work done! Well, the computer industry is marketing that capability now in the form of high-end video cards – and for a bargain price – with more and better technology on the market horizon. As the industry evolves to become more oriented toward multi-core and multi-threaded hardware; video card manufacturers are attempting to transition from a niche to multi-purpose market. One of the products currently getting attention is the Nvidia Tesla family of products based on the Tesla GPGPU (general purpose graphics processing unit). This card contains 128 processor computing core engines advertised as having the ability to deliver an aggregate 518 billion single-precision floating operations per second (518 Gflop), which is being introduced at a $1499 MSRP price-point. Nvidia also offers other commodity graphics cards, such as the GeForce 8800, which appear on paper to have roughly the same performance for roughly half the price – although with half the memory (768M vs the Tesla 1.5 GB). This highlights how the Tesla GPGPUs are essentially redesigned graphics cards (with no video capability, increased memory, and clock changes) that fit into PCI-Express slots in your motherboard. If you believe Nvidia’s claims, two Tesla cards will - for the right applications - turn your lab workstation into a teraflop capable supercomputer. Double-precision versions are projected for a late 2007 introduction with expected 2008 delivery. The Nvidia Tesla GPGPU is one step forward in the many-core revolution that is happening in the computer industry. Instead of making two or four processing cores available to the user, many-core processors offer tens or hundreds of processing cores. Many-core processors promise to provide very high performance-per-dollar and performance-per-watt for many computational workloads. Intel is working on their version of many-core processors but delivery dates appear to be several years in the future. Last year Intel made a large splash with their proof-of-concept teraflop 80-core chip, which they announced might be available sometime in 2011. Intel is also working on something similar to the Nvidia Tesla – codename Larrabee – which will perform in the teraflop range and has a release date of sometime around 2009 or 2010. Larrabee is supposed to have 16 – 24 cores and several nice features. Bottom line: A teraflop lab computer is feasible today as the programmable Nvidia GeForce 8 and Quadro family of graphics cards are available now, Tesla cards will be shipping, and exciting many-core architectures are on the horizon from a number of vendors. Definitely, the potential for parallel processing systems is huge, and GPGPUs certainly provide parallel processing, but are there enough applications out there to take them mainstream and make it more appealing to businesses other than just research firms? Only time will tell as more applications are developed to utilize this computational capability. Right now, programming is required. Recently Google purchased PeakStream, a firm that engaged in abstracting the task of running multiple threads to software with specific GPGPU applicability. However, Google is a visionary software company. Instrument vendors and much of the software industry are still in the early stages of the transition to multi-threaded many-core data processing. Applications that exploit the full potential of parallel processing systems, and GPGPUs in particular, really don’t exist in today’s market. The development of Matlab plug-ins is a very positive sign for the future of GPGPUs and is indicative of Nvidia’s sense of where the market is headed.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 921559
- Report Number(s):
- PNNL-SA-56476; KP1504020; TRN: US200804%%666
- Journal Information:
- Scientific Computing, 24(10):34, Vol. 24, Issue 10
- Country of Publication:
- United States
- Language:
- English
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