NVIDIA Tesla C870

The NVIDIA® Tesla™ C870 GPU computing processor is a massively multi-threaded processor architecture that is ideal for high performance computing (HPC) applications used by scientists, engineers, and other technical professionals.

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Products / High Performance Computing Solutions / NVIDIA Tesla C870

Overview

Specifications

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The Tesla C870 GPU computing processor transforms a standard workstation into a personal supercomputer. With 128 streaming processor cores, the CUDA C-language development environment and developer tools, and a range of applications already ported, the Tesla C870 enables professionals to develop applications faster and solve problems that traditionally required access to a shared server cluster.

Image Courtesy of Evolved Machines.

Massively Multi-threaded Processor Architecture
Solve compute problems at your workstation that previously required a large cluster

128 Floating Point Processor Cores
Achieve up to 350 GFLOPS of performance (512 GFLOPS peak) with one C870 GPU

Multi-GPU Computing
Solve large-scale problems by dividing it across multiple GPUs

Shared Data Memory
Groups of processor cores can collaborate using shared data

High Speed, PCI-Express Data Transfer
Fast and high-bandwidth communication between CPU and GPU

Image Courtesy of University of Illinois at Urbana-Champaign.

To download the Product Overview PDF - please click here. (1.7 MB PDF)


Features	Benefits
Massively parallel many core architecture	128 processor cores that can execute thousands of concurrent threads to deliver unprecedented application performance
Widely accepted, easy to learn CUDA C parallel programming environment	Easily express application parallelism to take advantage of the GPU’s many core architecture
Scale to multiple GPUs and harness the performance of 1000s of processor cores	Get very high application performance by mapping the application to multiple GPUs
128 IEEE single precision floating point units	Achieve up to 350 GFLOPs of sustained performance (512 GFLOPs peak)
384-Bit Memory Interface from GPU to on-board memory	Fast GDDR3, 384-bit memory interface delivers 76.8 GB/sec memory bandwidth for blistering data transfer
1.5 GB of on-board memory with each GPU	Transfer data less often and perform larger computations on a larger working data set
High Speed, PCI Express Data Transfer	Computing applications benefit from the high data transfer rate possible through standard PCI-Express architecture
Parallel shared memory	Low latency memory shared by groups of processors to enable efficient collaboration among them
Tesla GPUs available in flexible form factor	Tesla add-in card, deskside, and 1U system enables deployment in a wide range of environments

Main | Features


Form Factor	ATX, 4.38" x 12.28", dual slot height
# of Tesla GPUs	1
# of Streaming Processor Cores	128
Frequency of Processor Cores	1.35 Ghz
Floating Point Precision	IEEE 754 single-precision floating point
Floating Point Performance	430 GFLOPs achievable with a C (CUDA) program (512 peak)
Total Dedicated Memory	1.5 GB at 800 Mhz
Memory Interface	384-bit GDDR3
Memory Bandwidth	76.8 GB/sec peak
Max Power Consumption	170W peak, 120W typical
System Interface	PCI Express x16 (Generation 1)
Auxiliary Power Connectors	Yes (2)
Thermal Solution	Active Fansink
Programming environment	CUDA


NVIDIA CUDA driver (required to run and develop CUDA applications)	Windows XP (32-bit and 64-bit)	Linux (32-bit and 64-bit)
CUDA Toolkit (required to run or develop CUDA applications)	Windows XP (32-bit and 64-bit)	Linux (32-bit and 64-bit)
CUDA SDK (contains code samples and utilities)	Windows XP (32-bit and 64-bit)	Linux (32-bit and 64-bit)