Since the NVIDIA reference platform specifies multiple GPUs, a Tesla desktop system will be much more powerful than a single-GPU workstation. The Tesla personal supers can be used as development and test platforms for Tesla clusters or as HPC production systems in their own right. NVIDIA’s strategy seems to be to stake out the middle of the market between workstations and PCs sequestered for GPU computing and full-blown Tesla-accelerated clusters, like the 170 teraflop system just announced by Tokyo Tech. Of course, researchers have been cobbling together GPU-accelerated workstations for awhile, but until now, users had no productized GPGPU desktop option other than PCs and workstations equipped with CUDA-compatible GPUs. NVIDIA has no new Tesla gear lined up for SC08 this week, but the company has come up with a hardware reference platform that can be used to build Tesla-equipped personal supercomputers. According to Patricia Harrell, AMD’s director of Stream Computing, they’ve received a lot of interest from both end users and the tier one OEMs. It’s meant to offer a lot of compute density, along with the flexibility of a standard host connection. Since the connection is optical fiber, the expansion box can use the full speed of the PCIe bus over distances of up to 50 meters. Up to 4 PCIe x16 buses connect the box to host servers, using optical interconnect technology developed by Aprius. Built by newcomer Aprius Inc., the Computational Acceleration System (CA8000) is a 4U box that can hold up to eight 9270 GPU boards, yielding an aggregate performance of 9.6 SP teraflops (1.9 DP teraflops). If you happen to be in Austin, Texas, this week for the SC08 conference, you can see one in action at AMD’s booth.ĪMD will also be demonstrating a FireStream-based expansion box, which will start shipping in early 2009. The new card will retail for $1,499, and will start shipping in a few weeks. Like the FireStream 9250, the 9270 uses a compact form-factor and can slide into both workstations and servers - anything with a PCIe 2.0 x16 slot. If the GPU ends up waiting for data from the host, this negates some of speedup realized by offloading computing onto the graphics chip. Memory capacity is a big deal in GPU acceleration since if the dataset doesn’t fit in local memory, the runtime system has to spend time shuffling data bytes back and forth between the CPU host and the accelerator board. The increased memory brings it back in line with the original FireStream 9170 board, but it still has just half the memory capacity of the latest Tesla gear from NVIDIA. And at 160W, the new 9270 runs just a tad hotter than the 9250. With 2GB of GDDR5 memory, the new board doubles the memory capacity and nearly doubles of bandwidth of its predecessor. By cranking up the clock speed on the GPU, the new offering boasts 1.2 single precision (SP) teraflops and 240 double precision (DP) gigaflops - 20 percent greater than the 9250. 13, the company unveiled the FireStream 9270, which is essentially a high-end version of the FireStream 9250, AMD’s original double-precision GPU card for HPC. Meanwhile, AMD has released its most powerful GPU computing board, the AMD FireStream 9270, and has also partnered with Silicon Valley startup Aprius to offer a 9.6 teraflop GPU expansion chassis.įirst AMD. These machines offer as much as 4 single precision teraflops of performance for the cost of a high-end workstation. Riding the success of the CUDA software platform, NVIDIA has partnered with a number of OEMs and system integrators to offer Tesla-equipped personal supercomputers. New GPGPU computing platforms are in the works at NVIDIA and AMD. Since 1987 - Covering the Fastest Computers in the World and the People Who Run Them
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