Tech4all group blog

NVIDIA® Tesla™: Personal Supercomputer

• Up to 960 Core Parallel Supercomputer on Your Desk, 250 Times Faster than a PC.
  • Up to 4 teraflops of compute capability for under $10,000.
  • Computation comparable to a large server cluster that fills a room.
  • 250 times faster than a multi-CPU core PC or workstation using traditional serial computing.
  • GPU parallelism designed to execute tens of thousands of concurrent threads.
  • Up to16 GB of dedicated compute memory meets the computing requirements of large datasets.
  • Single- and double-precision floating point.
  • Scalable architecture meets computational demands of complex scientific applications.
• Based on Revolutionary NVIDIA® CUDA® Parallel Computing Architecture.
  • Unlocks the power of GPU parallel computing.
  • Over 25,000 application developers worldwide using CUDA.
  • Over 100,000,000 CUDA-enabled processors shipped.
• Accessible to Everyone
  • Supercomputing available to anyone, anytime.
  • Iterate faster; discover more.
    • Computing whenever you need it. No need to ask permission to an administrator.
  • Buy it anywhere, put it anywhere.
    • Plugs into standard power strip.

Tesla Architecture

• Massively-parallel many-core architecture
• 240 scalar processor cores per GPU
• Integer, single-precision and double-precision floating point operations
• Hardware Thread Execution Manager enables thousands of concurrent threads per GPU
• Parallel shared memory enables processor cores to collaborate on shared information at local cache performance
• Ultra-fast GPU memory access with 102 GB/s peak bandwidth per GPU
• IEEE 754 single-precision and double-precision floating point
• Each Tesla C1060 GPU delivers 933 GFlops Single Precision and 78 GFlops Double Precision performance

Software Development Tools

• C language compiler, debugger, profiler, and emulation mode for debugging
• Standard numerical libraries for FFT (Fast Fourier Transform), BLAS (Basic Linear Algebra Subroutines), and CuDPP (CUDA Data Parallel Primitives)

Product Details

• 3 or 4 Tesla C1060 Computing Processors with 4GB of dedicated memory per GPU
• 2.33 GHz+ Quad-core AMD Phenom or Opteron, -- OR -- Quad-core Intel Core 2 or Xeon
• Minimum system memory: 12 GB for 3 Tesla C1060s and 16 GB for 4 Tesla C1060s (at least 4GB per Tesla C1060)
• 12GB+ system memory (at least 4GB per Tesla C1060)
• 1200-1350 Watt Power supply
• Acoustics < 45dbA

Supported Platforms

• Microsoft® Windows® XP 64-bit and 32-bit (64-bit recommended)
• Linux® 64-bit and 32-bit (64-bit recommended)
• Red Hat Enterprise Linux 4 and 5
• SUSE 10.1, 10.2 and 10.3