Nvidia Tesla M2090 6GB TCSM2090-PB Data Sheet
Product codes
TCSM2090-PB
TESLA
™
M-CLASS
GPU CoMPUTinG ModULES
ACCELErATinG SCiEnCE
NVIDIA TESLA | DATASHEET | AUG 11
MoLEcULAr DyNAMIcS
oIL & GAS
Based on the cUDA
™
architecture codenamed “Fermi,” the Tesla
™
M-class GPU computing Modules are the world’s fastest parallel
computing processors for high performance computing (HPc). Tesla
GPU’s high performance makes them ideal for seismic processing,
biochemistry simulations, weather and climate modeling, signal
processing, computational finance, cAE, cFDand data analytics.
computing processors for high performance computing (HPc). Tesla
GPU’s high performance makes them ideal for seismic processing,
biochemistry simulations, weather and climate modeling, signal
processing, computational finance, cAE, cFDand data analytics.
Accelerate your science with NVIDIA®
Tesla
Tesla
™
20-series GPUs. A companion
processor to the cPU in the server, Tesla
GPUs speed up HPc applications by 10x.
Based on the Fermi architecture, these
GPUs feature up to 665 gigaflops of double
precision performance, 1 teraflop of single
precision performance, Ecc memory
error protection, and L1 and L2 caches.
GPUs speed up HPc applications by 10x.
Based on the Fermi architecture, these
GPUs feature up to 665 gigaflops of double
precision performance, 1 teraflop of single
precision performance, Ecc memory
error protection, and L1 and L2 caches.
The Tesla M-class GPU modules are
integrated into GPU-cPU servers
from oEMs. This gives data center IT
staff much greater choice in how they
deploy GPUs, with a wide variety of
rackmount and blade systems and with
remote monitoring and management
capabilities – enabling large data
center, scale-out deployments.
integrated into GPU-cPU servers
from oEMs. This gives data center IT
staff much greater choice in how they
deploy GPUs, with a wide variety of
rackmount and blade systems and with
remote monitoring and management
capabilities – enabling large data
center, scale-out deployments.
TEcHNIcAL SPEcIFIcATIoNS
* Note: With Ecc on, 12.5% of the GPU memory is used for Ecc bits. So, for
example, 3 GB total memory yields 2.625 GB of user available memory
with Ecc on.
example, 3 GB total memory yields 2.625 GB of user available memory
with Ecc on.
Tesla M2090
665 Gigaflops
1331 Gigaflops
512
6 GigaBytes
177 GBytes/sec
6 GigaBytes
177 GBytes/sec
Tesla M2050
515 Gigaflops
1030 Gigaflops
448
3 GigaBytes
148 GBytes/sec
3 GigaBytes
148 GBytes/sec
Peak double precision floating
point performance
Peak single precision floating
Peak single precision floating
point performance
CUDA cores
Memory size (GDDR5)
Memory bandwidth (ECC off)
CUDA cores
Memory size (GDDR5)
Memory bandwidth (ECC off)
Tesla M2070 / M2075
515 Gigaflops
1030 Gigaflops
448
6 GigaBytes
150 GBytes/sec
6 GigaBytes
150 GBytes/sec