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.
Take advantage of the newest analysis,
simulation, and rendering tools within
industry-leading applications and see
results in as little as half the time. Tesla
C2075 companion processors deliver
parallel processing power right at the
desk, capable of streamlining the way
users work every day. This means you
can now explore, discover and deliver
higher-quality projects faster than you
ever thought possible.
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.
ECC Memory
Meets a critical requirement for computing accuracy and reliability for worksta-
tions. 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 dara 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 enviroment 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.
High speed, PCIe GEN 2.0
data transfer
Maximizes bandwidth between the host system and the Tesla processors. En-
ables Tesla products to work with virtually any PCIe-compliant host system with
an open PCIe x16 slot.
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