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.
Download the spec sheet
| NVIDIA Tesla C2075 Features |
| Features |
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. |
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ECC Memory |
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. |
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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. |
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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. |
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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. |
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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. |
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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" GPU's innovative architecture. NVIDIA Parallel Nsight GPU debugging tool is available for Microsoft Visual Studio developers. |
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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. |
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| Specification |
| Form Factor |
| 9.75+ PCIe x16 form factor |
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| CUDA Cores |
| 448 |
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| Frequency of CUDA Cores |
| 1.15 GHz |
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| Double Precision floating point performance (peak) |
| 515 Gflops |
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| Single Precision floating point performance (peak) |
| 1.03 Tflops |
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| Total Dedicated Memory |
| 6GB GDDR5 |
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| Memory Speed |
| 1.5 Ghz |
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| Memory Interface |
| 384-bit |
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| Memory Bandwidth |
| 144 GB/sec |
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| Power Consumption |
| 225W TDP |
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| System Interface |
| PCIe x16 Gen2 |
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| Thermal Solution |
| Active Fansink |
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| Display Support |
| Dual-Link DVI-I: 1, Maximum Display Resolution: 1600 x 1200 pixels |
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