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Supporting Platforms
- NVIDIA® Tesla™ tested system*
- Microsoft® Windows® XP (32-bit) (Available on Tesla C870 and Tesla D870 only)
- Linux® (64-bit and 32-bit)
- Red Hat Enterprise Linux 4 and 5
- SUSE 10.1, 10.2 and 10.3 (coming soon)
- Massively-parallel computing architecture with 128 multi-threaded processors per GPU
- Scalar thread processor with full integer and floating point operations
- Thread Execution Manager enables thousands of concurrent threads per GPU
- Parallel Data Cache enables processors to collaborate on shared information at local cache performance
- Ultra-fast memory access with 76.8 GB/sec. peak bandwidth per GPU
- IEEE 754 single-precision floating point
- Scalable from one to thousands of GPUs
- Available in GPU computing processor, deskside GPU computing system and 1U rack-mount GPU computing system
- C language compiler, profiler and emulation mode for debugging
- Standard numerical libraries for FFT (Fast Fourier Transform) and BLAS (Basic Linear Algebra Subroutines)
- Tesla C870 GPU Computing Processor
- One GPU (128 thread processors)
- 1.5 GB dedicated memory
- Fits in one full-length, dual slot with one open PCI Express x16 slot
- Tesla D870 Deskside GPU computing system
- Two GPUs (128 thread processors per GPU)
- 3 GB system memory (1.5 GB dedicated memory per GPU)
- Quiet operation (40dB) suitable for office environment
- Connects to host via cabling to a low power PCI Express x8 or x16 adapter card
- Optional rack mount kit
- Tesla S870 GPU Computing System
- Four GPUs (128 thread processors per GPU)
- 6 GB of system memory (1.5 GB dedicated memory per GPU)
- Standard 19”, 1U rack-mount chassis
- Connects to host via cabling to a low power PCI Express x8 or x16 adapter card
- Configuration: 2 PCI Express connectors driving 2 GPUs each (4 GPUs total)
