Tesla

NAMD on Tesla GPUs

 
 

The Team at University of Illinois at Urbana-Champaign (UIUC) has been enabling CUDA-acceleration on NAMD since 2007. They have performed scaling experiments on the NCSA Tesla-based Lincoln cluster and demonstrated that 4 Tesla GPUs can outperform a cluster with 16 quad core CPUs.

Download and Installation

Benchmark Data

NAMD scales very well on a Tesla GPU cluster as demonstrated by these results.

NAMD Results on CPU vs GPU Clusters
Data courtesy of Theoretical and Computational Bio-physics Group, UIUC

Technical Papers

There are several papers on GPU acceleration in NAMD and VMD available at the UIUC website.
To learn more, you can also refer to the NVIDIA molecular dynamics page to learn more about accelerating molecular dynamics applications using CUDA.

Presentations

Discussion Forums

Interviews / Videos

GPU SOLUTIONS

The Tesla Bio Workbench applications can be deployed on GPU-based desktop personal supercomputers or in data center solutions. Built on the revolutionary massively parallel CUDA architecture, these solutions are designed to accelerate the pace of computational science.

RECOMMENDED HARDWARE CONFIGURATION

Desktop Workstation Configuration Data Center Configuration
  • GPUs
    • 4 Tesla C1060 Computing
  • CPU and Main Memory
    • 2.33 GHz x86 CPU
    • >16 GB (4 GB main memory per Tesla C1060 GPU)
  • GPUs per node
    • Either Tesla S1070 (with 4 GPUs in a 1U) or hybrid servers with M1060 GPUs
  • CPU and Main Memory
    • 2.33 GHz x86 CPU per server
    • 16 GB per server

Tesla Personal Supercomputer   Tesla GPU Computing Clusters
WORKSTATION SOLUTIONS
TESLA PERSONAL SUPERCOMPUTER

For personal supercomputing at your desk
Learn more > Where to buy >
 
DATA CENTER SOLUTIONS
TESLA GPU COMPUTING CLUSTERS

For computing with large-scale installations
Learn more > Where to buy >