DALCO nVidia TESLA based Preconfigured Clusters
Supercharge your cluster with Tesla CUDA-based GPUs
DALCO's Tesla Preconfigured Clusters deliver supercomputing performance at a low cost and low power while using far fewer systems than standard CPU-only clusters. Powered by the NVIDIA® Tesla™ S1070 Computing System, this four teraflop 1U system with the Tesla T10 GPUs is based on the CUDA parallel architecture. With 4 GB of memory per GPU, support for IEEE 754 single & double floating point precision, and a fast 102 GB/sec GDDR3 interface to the memory, the S1070 1U speeds the transition to energy-efficient parallel computing and scales to solve the world's most important computing challenges with speed and accuracy. Successfully deployed at research institutes, universities, and enterprises.
DALCO offers several configurations of the TeslaTM preconfigured clusters and we can customize them to your needs:
| 32 TeraFlop DALCO GPU-Cluster | 16 TeraFlop DALCO GPU-Cluster | |
|---|---|---|
| Configurations | 8 TeslaTM S1070 Preconfigured Cluster | 4 TeslaTM S1070 Preconfigured Cluster |
| GPUs | 32 TeslaTM T10 GPUs | 16 TeslaTM T10 GPUs |
| Compute Node | 8 DALCO r2164 Compute Node with Dual-socket Quad-core AMD OpteronTM or Intel XeonTM | 4 DALCO r2164 Compute Node with Dual-socket Quad-core AMD OpteronTM or Intel XeonTM |
| Master Node | 1 DALCO r2164 Master Node with Dual-socket Quad-core AMD OpteronTM or Intel XeonTM | 1 DALCO r2164 Master Node with Dual-socket Quad-core AMD OpteronTM or Intel XeonTM |
| Memory | 256 GB GPU memory Up to 256 GB CPU memory | 128 GB GPU memory Up to 128 GB CPU memory |
| Storage | Up to 64 TB S-ATAII, SAS or SSD drives Panasas® or Lustre® parallel file system option | Up to 32 TB SATAII, SAS or SSD drives Panasas® or Lustre® parallel file system option |
| Interconnect | Infiniband DDR or QDR | Infiniband DDR or QDR |
| Network | 10/100/1000 Gigabit Switch | 10/100/1000 Gigabit Switch |
Installed Software
The DALCO TeslaTM preconfigured cluster comes preinstalled with:
- Redhat Enterprie Linux 5.x, SuSE SLES
- CUDA 2.2 Toolkit and SDK
- DALCO Cluster Management Suite
CUDA Applications
The CUDA-based TeslaTM GPUs give speedups of up to 250x on applications ranging from MATLAB to computational fluid dynamics, molecular dynamics, quantum chemistry, imaging, signal processing, bio-informatics, and so on. [Click here to learn more] about these speedups with links to application downloads.
GPU Software Development Tools
[Click here to find out more] about the C-based software development tools and various libraries for GPUs.
