Overview
Access the power of GPU computing with off-the-shelf, ready to deploy TESLA GPU SimCluster.
These preconfigured solutions from NVIDIA provide a powerful tool for researchers and scientists to advance their science through faster simulations. SimCluster is the easiest way to start using GPUs that offer supercomputing scale HPC performance at substantially lower costs and power. Experience a significant performance increase in a wide range of applications from various scientific domains. Supercharge your research with TESLA GPU SimCluster today!
What is GPU Computing?
GPU computing is the use of a GPU (graphics processing unit) to do general purpose scientific and engineering computing. The model for GPU computing is to use a CPU and GPU together. The sequential part of the application runs on the CPU and the computationally-intensive part runs on the GPU. GPU computing is enabled by the massively parallel architecture of NVIDIA's GPUs called the CUDA architecture. The CUDA architecture consists of 100s of processor cores that operate together to crunch through the data set in the application.
AMBER and NAMD along with several other MD applications support GPU computing. From the user's perspective, these applications just run faster using the GPU to boost performance.
Test-Drive the Tesla MD SimCluster Today!
Key Features
- Optimised for job throughput
- Designed for Multi-user
- 14U Rack Cabinet
- 1 x Head node
- 8 x 1U GPU Compute Nodes each consisting of:
- 2 x M2090 GPUs
- 1 x Intel Xeon E5645 CPU
- 48GB DDR3 1333MHz ECC Registered memory
- 10GbE Connectivity with 24-Port Switch