Industry’s First Dedicated Stream Processor !!


The true computing geeks in the house are about to need adult diapers: AMD’s launching a dedicated stream processor, the FireStream 9170, and an accompanying SDK today, which will be available in Q108. Granted, this 55nm “world’s first Stream GPU with double-precision floating point technology” will run you two grand, but you’ll be getting 500 GFLOPS at under 150 watts power draw, but you’ll get all the insane math-crunching benefits of stream processing that your current number-crunching rig isn’t seeing, despite the eight 8800s you’ve got jury-rigged into the thing.

Read more about stream processing here

AMD FireStream 9170 Specifications

  • Powered by next-generation ATI GPU from AMD
  • Parallel processing architecture with 320 stream cores
  • Up to 500 GFLOPs single precision performance
  • 2GB GDDR3 on-board memory
  • Double Precision Floating Point
  • PCIe 2.0 x16 interface
  • < 150W power consumption
  • Memory export
  • BIOS settings optimized for stream processing
  • API and OS Support
  • Windows XP, XP64
  • Linux 32 and Linux 64
System Requirements
  • PCI Express® based server or workstation with available x16 lane graphics slot
  • 500W or greater power supply
  • 512MB of system memory
Optimized for Computation
  • Double-precision floating point for scientific and engineering codes
  • 2GB on-board memory
  • 320 stream cores drive up to 500 GFLOPS single-precision performance
  • Asynchronous DMA, allowing data transfers without interrupting streams processor or CPU
Accelerating data-parallel algorithms in a variety of applications
  • Seismic processing
  • Financial analysis
  • Engineering analysis
  • Rendering
  • Computational chemistry
  • Genetic research
  • Physics
  • Video editing
  • Security
AMD Warranty and Support
  • Enterprise-level support
  • Three year limited product repair/replacement warranty
  • Toll-free phone and email access to technical support team

AMD FireStream stream processors deliver the tremendous parallel processing power of the GPU to compute-intensive applications for scientists, engineers and consumers. Using this leading-edge technology, developers can dramatically increase the performance of their critical algorithms, allowing users to get faster results or work on larger problems.


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