Nvidia Tesla - Specifications and Configurations

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
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.

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