Difference between revisions of "Accelerator Research Cluster"
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| − | The Accelerator Research Cluster is a technology evaluation cluster with a combination of 14 IBM PowerXCell 8i "Cell" nodes and 8 Intel x86_64 "Nehalem" nodes containing NVIDIA GPUs. | + | The Accelerator Research Cluster (ARC) is a technology evaluation cluster with a combination of 14 IBM PowerXCell 8i "Cell" nodes and 8 Intel x86_64 "Nehalem" nodes containing NVIDIA GPUs. |
The QS22's each have two 3.2GHz "IBM PowerXCell 8i CPU's, where each CPU has 1 Power Processing Unit (PPU) and 8 Synergistic Processing Units (SPU), and | The QS22's each have two 3.2GHz "IBM PowerXCell 8i CPU's, where each CPU has 1 Power Processing Unit (PPU) and 8 Synergistic Processing Units (SPU), and | ||
32GB of RAM per node. The Intel nodes have two 2.53GHz 4core Xeon X5550 CPU's with 48GB of RAM per node and 3 contain Nvidia 9800GT video cards. | 32GB of RAM per node. The Intel nodes have two 2.53GHz 4core Xeon X5550 CPU's with 48GB of RAM per node and 3 contain Nvidia 9800GT video cards. | ||
Revision as of 16:12, 13 April 2010
| Accelerator Research Cluster (ARC) | |
|---|---|
| Installed | June 2010 |
| Operating System | Linux (RHEL 5.4) |
| Interconnect | Infiniband,GigE |
| Login/Devel Node | cell-srv01 (from login.scinet) |
The Accelerator Research Cluster (ARC) is a technology evaluation cluster with a combination of 14 IBM PowerXCell 8i "Cell" nodes and 8 Intel x86_64 "Nehalem" nodes containing NVIDIA GPUs. The QS22's each have two 3.2GHz "IBM PowerXCell 8i CPU's, where each CPU has 1 Power Processing Unit (PPU) and 8 Synergistic Processing Units (SPU), and 32GB of RAM per node. The Intel nodes have two 2.53GHz 4core Xeon X5550 CPU's with 48GB of RAM per node and 3 contain Nvidia 9800GT video cards.
Login
First login via ssh with your scinet account at login.scinet.utoronto.ca, and from there you can proceed to cell-srv01 which is currently the gateway machine.
Compile/Devel/Compute Nodes
Cell
You can log into any of 12 nodes blade[03-14] directly to compile/test/run Cell specific or OpenCL codes.
See the Cell Devel Info page for Cell specific details.
Nehalem (x86_64) & GPU
You can log into any of 8 nodes cell-srv[01-08] directly however each of the nodes have differing configurations.
- cell-srv01 - login node & nfs server, GigE connected
- cell-srv[02-05] - no GPU, GigE connected
- cell-srv[06-07] - 1x NVIDIA 9800GT GPU, Infiniband connected
- cell-srv08 - 2x NVIDIA 9800GT GPU, GigE connected
See the GPU Devel Info page for GPU specific details.
Local Disk
This test cluster currently cannot see the global /home and /scratch space so you will have to copy (scp,etc..) your code to a separate local/home dedicated for this cluster. Also initially you will probably want to copy/modify your scinet .bashrc, .bashrc_profile, and .ssh directory onto this system.