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PeakStream Is Extraordinarily Serious Runtime for HPC


By Edward J. Correia
October 1, 2006 — 
PeakStream is not about playing games. But the new company has its eye on IBM’s Cell processor and high-speed graphics processor units, even though those circuits are being used today mainly to run entertainment software.

Former executives of Sun Microsystems, VMware and Nvidia, the graphics accelerator chip maker, have joined to form PeakStream Inc. Flush with US$17 million in Series B funding, the company in September unveiled the PeakStream Platform, a runtime solution for high-performance computing that it claims abstracts the complexities and pitfalls of programming for multiple processors or cores while improving application performance by more than twentyfold.

The all-software solution includes the PeakStream Server, which installs on top of an Intel-based machine with an optional board containing one or more graphics processor units (GPUs). “This is substantial technology that allows you to run an application on top of a graphics processor,” said Matt Papakipos, PeakStream’s CTO and former architecture lead with Nvidia.

An evaluation version for Linux was set to be released on Sept 18; general availability is scheduled before the end of this year. Pricing is set at $2,000 per server.

Papakipos said that to take advantage of the PeakStream APIs, a developer need only include the appropriate PeakStream libraries in new or existing C/C++ apps. “A virtual machine provides an abstraction layer on multiple types of CPUs and GPUs so code can execute anywhere,” he said. Initial VMs will support Cell, multicore 32- and 64-bit Xeon and ATI GPUs (now owned by AMD). “This is the magic of the technology; apps can run anywhere with no rewrite,” Papakipos claimed, adding that the VM handles matrix math, core math, signal processing and user-developed intrinsics.

After reviewing a PeakStream white paper, Steven Wallach, a supercomputer designer and consultant to Los Alamos National Laboratory in New Mexico, said he believes the technology has potential. “For a certain limited set of applications, they could probably see significant increases,” in performance, he said, provided they’re 32-bit apps performing lots of floating-point operations. “GPUs are 32-bit, single-precision processors,” he said.

There is a degree of work involved, but far less than would be without the VM, Papakipos said, and with greatly reduced risk. “The process of taking an array of data and [manually] assigning it to multiple cores is program-directed,” he said, and by design creates the need to lock one processor while another finishes its work. “PeakStream is different. We steer clear of the issues that cause multicore programs to hang.” Arrays are treated as first-class objects and are completely atomic, he explained. “Each operation is completed before the next one begins. The programmer is not assigning work to processors, so it’s impossible to get those race and deadlock conditions.”

ALL APPS MUST CHANGE
PeakStream introduces a technique it calls stream programming, in which program parallelism is expressed in arrays. “Arrays match the character of high-performance computing because [HPC apps] tend to be data-intensive and have many mathematical operations,” said Papakipos. The runtime handles work scheduling and read/write operations with non-uniform graphics and system memory. Latencies associated with movement of data from system to graphics memory are improved by a shared cache.

“We’ve also included the ability to do explicit reads and writes to graphics memory” or to main memory, said Michael Mullany, PeakStream’s vice president of marketing. “That’s an advantage because it gives the programmer more control of what is being moved to memory and when,” he said, adding that specific computations can be earmarked for processing where they will be handled most quickly and efficiently. “We recommend that arrays [contain] at least 10,000 elements for optimal performance,” he added. Unmodified applications will run, but will not be accelerated.

Based on technology developed at Stanford, stream and array-oriented languages have been in use in HPC and academia for decades. “But we’re the first commercial stream programming platform, and the model we are introducing is for doing high-performance computing.”


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