Specifications and Configurations
Configuration | Model | # of GPUs | Core clock in MHz (each) |
Shaders | Memory | Processing Power (peak) GFLOPs |
Compute capability4 | TDP watts | Form factor and features |
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Thread Processors (total) | Clock in MHz (each) | Bandwidth max (GB/s) | Bus type | Bus width (bit, each GPU) | Total size (MiB) | Clock (MHz) | Single Precision (SP) Total (MUL+ADD+SF) | Single Precision (SP) MAD (MUL+ADD) | Double Precision (DP) FMA | |||||||
GPU Computing Processor1 |
C870 | 1 | 600 | 128 | 1350 | 76.8 | GDDR3 | 384 | 1536 | 1600 | 518.4 | 345.6 | 0 | 1.0 | 170.9 | Full-height video card |
Deskside Supercomputer1 | D870 | 2 | 600 | 2 × 128 (256) | 1350 | 153.6 | GDDR3 | 384 | 3072 | 1600 | 1036.8 | 691.2 | 0 | 1.0 | 520 | Deskside system or Rack unit |
GPU Computing Server1 | S870 | 4 | 600 | 4 × 128 (512) | 1350 | 307.2 | GDDR3 | 384 | 6144 | 1600 | 2073.6 | 1382.4 | 0 | 1.0 | 1U Rack | |
C1060 Computing Processor 2 |
C1060 | 1 | 602 | 240 | 1300 | 102.4 | GDDR3 | 512 | 4096 | 1600 | 933.12 | 622.08 | 77.76 | 1.3 | 187.8 | 2 slot video card |
S1075 1U GPU Computing Server3,4 |
S1070 | 4 | 602 | 4 × 240 (960) | 1440 | 409.6 | GDDR3 | 512 | 16384 | 1600 | 4147.2 | 2764.8 | 345.6 | 1.3 | 1U Rack IEEE 754-2008 capabilities |
|
C2050/C2070/C2075 GPU Computing Processor |
C2050/C2070/C2075 | 1 | 575 | 448 | 1150 | 144 | GDDR5 | 384 | 3072/61445 | 1500 | 1288 | 1030.46 | 515.2 | 2.0 | 238/247/225 | Full-height video card IEEE 754-2008 FMA capabilities |
M2050 GPU Computing Module |
M2050 | 1 | 575 | 448 | 1150 | 148.4 | GDDR5 | 384 | 30725 | 1546 | 1288 | 1030.46 | 515.2 | 2.0 | 225 | Computing Module IEEE 754-2008 FMA capabilities |
M2070/M2070Q GPU Computing Module |
M2070/M2070Q | 1 | 575 | 448 | 1150 | 150.336 | GDDR5 | 384 | 61445 | 1566 | 1288 | 1030.46 | 515.2 | 2.0 | 225 | Computing Module IEEE 754-2008 FMA capabilities |
M2090 GPU Computing Module |
M2090 | 1 | 650 | 512 | 1301 | 177 | GDDR5 | 384 | 61445 | 1848 | ? | 1332.2 | 666.1 | 2.0 | 225 | Computing Module IEEE 754-2008 FMA capabilities |
S2050 1U GPU Computing System |
S2050 | 4 | 575 | 4 × 448 (1792) | 1150 | 4 × 148.4 (593.6) | GDDR5 | 384 | 122885 | 3092 | 5152 | 4121.66 | 2060.8 | 2.0 | 900 | 1U Rack IEEE 754-2008 FMA capabilities |
K10 GPU Computing Module |
K10 / GK104 | 2 | 745 | 1536 per GPU | 256 per GPU | 160 per GPU | GDDR5 | - | 4096 per GPU | 2500 | 2288 per GPU | - | 95 per GPU | 3.0 | 225 | Computing Module IEEE 754-2008 FMA capabilities |
K20 GPU Computing Module | GK110 | 1 | 745 | 2496 | 706 | 208 | GDDR5 | 384 | 5120 | 2560 | 3520 | - | 1170 | 3.5 | 225 | Computing Module IEEE 754-2008 FMA capabilities |
K20X GPU Computing Module | GK110 | 1 | 735 | 2688 | 732 | 250 | GDDR5 | 384 | 6144 | 5200 | 3950 | 384 | 1310 | 3.5 | 235 | Computing Module IEEE 754-2008 FMA capabilities |
Notes
- 1 Specifications not specified by NVIDIA are assumed to be based on the GeForce 8800GTX
- 2 Specifications not specified by NVIDIA are assumed to be based on the GeForce GTX 285
- 3 A host system/server is required to connect to the 1U GPU computing server by the PCI Express card
- 4 Core architecture version according to the CUDA programming guide.
- 5 With ECC on, a portion of the dedicated memory is used for ECC bits, so the available user memory is reduced by 12.5%. (e.g. 3 GB total memory yields 2.625 GB of user available memory.)
- 6 Fermi implements the new fused multiply–add (FMA) instruction for both 32-bit single-precision and 64-bit double-precision floating point numbers (GT200 supported FMA only in double precision) that improves upon multiply-add by retaining full precision in the intermediate stage.
- For the basic specifications of Tesla, refer to the GPU Computing Processor specifications.
- Performance figures are for single-precision except where noted.
- NVIDIA Tesla Supercomputers are also available with up to 8x Fermi GPUs from Manufacturers.
Read more about this topic: Nvidia Tesla
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