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GPU Computing TESLA
GPU Computing with TESLA Nvidia, 240 GPU processors that can enlighten your processing capability.
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NVIDIA Tesla C1060
฿46,500.00
TESLA C1060 is the power of 240 parallel processors that empower your workstation to reach new levels of computational agility.
Since the TESLA is a product that can be used in conjunction with CUDA ready programs and applications, of which list are expanding daily, the general availibility of such a powerful card is mind blowing.
Companies world wide have used TESLA in their business process to fasten up and they are saving in the 100,000's of thousands of dollars if not millions by time and energy consumed when compared to normal processes.
Learn More
Since the TESLA is a product that can be used in conjunction with CUDA ready programs and applications, of which list are expanding daily, the general availibility of such a powerful card is mind blowing.
Companies world wide have used TESLA in their business process to fasten up and they are saving in the 100,000's of thousands of dollars if not millions by time and energy consumed when compared to normal processes.
Learn More
NVIDIA Tesla C2050
Regular Price: ฿95,000.00
Special Price: ฿94,500.00
TESLA C2050 is the power of 554 parallel processors that empower your workstation to reach new levels of computational agility.
GPUs powered by the Fermi-generation of the CUDA architecture Delivers cluster performance at 1/10th the cost and 1/20th the power of CPU-only systems based on the latest quad core CPUs.
448 CUDA Cores 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. Single precision peak performance is over a Teraflop per GPU.
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.
Desktop Cluster Performance Solves large-scale problems faster than a small server cluster on a single workstation with multiple GPUs.
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 GigaThread™ Engine Maximizes the throughput by faster context switching that is 10X faster than previous architecture, concurrent kernel execution, and improved thread block scheduling.
Asynchronous 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” GPU’s innovative architecture. NVIDIA Parallel Nsight™ 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 systems to work with virtually any PCIe-compliant host system with an open PCIe x16 slot. Learn More
GPUs powered by the Fermi-generation of the CUDA architecture Delivers cluster performance at 1/10th the cost and 1/20th the power of CPU-only systems based on the latest quad core CPUs.
448 CUDA Cores 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. Single precision peak performance is over a Teraflop per GPU.
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.
Desktop Cluster Performance Solves large-scale problems faster than a small server cluster on a single workstation with multiple GPUs.
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 GigaThread™ Engine Maximizes the throughput by faster context switching that is 10X faster than previous architecture, concurrent kernel execution, and improved thread block scheduling.
Asynchronous 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” GPU’s innovative architecture. NVIDIA Parallel Nsight™ 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 systems to work with virtually any PCIe-compliant host system with an open PCIe x16 slot. Learn More
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