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NVIDIA Tesla C2075 6GB 384-bit GDDR5 PCIe 2.0 x16 1.03 Tflops Workstation Video Card Images from retail item, box contents may vary.

NVIDIA Tesla C2075 6GB 384-bit GDDR5 PCIe 2.0 x16 1.03 Tflops Workstation Video Card

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  • CUDA 448
  • 6GB DDR5
  • Dual-Link DVI-I
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Learn more about the NVIDIA 900-21030-2221-100

General

Brand
NVIDIA
Model
900-21030-2221-100

Interface

Interface
PCI Express 2.0 x16

Chipset

Chipset Manufacturer
NVIDIA
GPU
Tesla C2075
CUDA Cores
448

Memory

Memory Clock
1.5GHz
Memory Size
6GB
Memory Interface
384-bit
Memory Type
GDDR5

3D API

DirectX
DirectX 11

Ports

DVI
1

Spec

Digital Resolution
Maximum Display Resolution 1600x1200
Cooler
With Fan
Dual-Link DVI Supported
Yes
Operating Systems Supported
Linux 32-bit, 64-bit Windows XP, Windows Vista, Windows 7 (32-bit and 64-bit)

Features

Features
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 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 PROG
RAMMING 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.

HIGH SPEED, PCIe GEN 2.0
DATA TRANSFER
Maximizes bandwidth between the host system and the Tesla processors.

Quick Info


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