Graphic Processing Unit Nodes
NVIDIA Tesla C2075 companion processor
Tesla companion processors bring the power of high performance computing to the workstation
With 448 application-acceleration cores per board, Tesla processors offload parallel computations from the CPU to dramatically accelerate the floating point calculation performance. By adding a Tesla processor, engineers, designers, and content creation professionals accelerate some of the most complex tools exponentially faster than by adding a second CPU. It’s an unbeatable solution for getting more done in less time.
Tesla C2075 spec sheet
Features and Benefits
|448 CUDA Cores
||Tesla C2075 delivers up to 515 Gigaflops of double-precision peak performance in each GPU, enabling a single workstation to deliver a Teraflop or more of performance.|
|Meets a critical requirement for computing accuracy and reliability for workstations. Offers protection of data in memory to enhance data integrity and reliability for applications. Register files, L1/L2 caches, shared memory, and DRAM all are ECC protected.|
|Up to 6GB of GDDR5 memory per GPU
|Maximizes performance and reduces data transfers by keeping larger data sets in local memory that is attached directly to the GPU.
|NVIDIA Parallel DataCache
|Accelerates algorithms such as physics solvers, ray-tracing, and sparse matrix multiplication where data addresses are not known beforehand. This includes a configurable L1 cache per Streaming Multiprocessor block and a unified L2 cache for all of the processor cores.
|NVIDIA Giga Thread Engine
|Maximizes the throughput by faster context switching that is 10X faster than previous architecture, concurrent kernel execution, and improved thread block scheduling.
|Dual Copy Engine enables true Asynchronous Data Transfer
|Turbocharges system performance by transferring data over the PCIe bus while the computing cores are crunching other data. Even applications with heavy data-transfer requirements, such as seismic processing, can maximize the computing efficiency by transferring data to local memory before it is needed.
|CUDA programming environment with broad support of programming languages and APIs
|Choose C, C++, OpenCL, DirectCompute, or Fortran to express application parallelism and take advantage of the Fermi GPUs innovative architecture. NVIDIA Parallel Nsight GPU debugging tool is available for Microsoft Visual Studio developers.
|High Speed, PCIe Gen 2.0 Data Transfer
|Maximizes bandwidth between the host system and the Tesla processors. Enables Tesla products to work with virtually any PCIe-compliant host system with an open PCIe x16 slot.
|9.75+ PCIe x16 form factor|
|Frequency of CUDA Cores|
|Double Precision floating point performance (peak)|
|Single Precision floating point performance (peak)|
|Total Dedicated Memory|
|PCIe x16 Gen2|
|Dual-Link DVI-I: 1, Maximum Display Resolution: 1600 x 1200 pixels|