Phi

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XeonPHI/K20 Test node
Tesla S2070 3qtr.gif
Installed April 2013
Operating System Linux Centos 6.4
Number of Nodes 1
Interconnect DDR Infiniband
Ram/Node 32 Gb
Cores/Node 8 with Xeon Phi & K20
Login/Devel Node arc09 (from arc01)
Vendor Compilers nvcc,pgcc,icc,gcc
Queue Submission none

This is a single test/devel node, part of the Accelerator Research Cluster, for investigating new accelerator technologies. It consists of a singele x86_64 nodes with one 8-core Intel Sandybridge Xeon E5-2650 2.0GHz CPU with 32GB of RAM per node. It has a single NVIDIA Tesla K20 GPU with CUDA Capability 3.0 (Kepler) with 2496 CUDA Cores and 5 GB of RAM as well as a single Intel Xeon Phi 5110P with


The nodes are interconnected with DDR Infiniband for MPI communications and disk I/O to the SciNet GPFS filesystems.


Login

First login via ssh with your scinet account at login.scinet.utoronto.ca, and from there you can proceed to arc01 which is the GPU development node and then to arc09.

Access to this machines is no enabled be default so please email support@scinet.utoronto.ca for access.

Devel/Compute

As this is a single node there is no queue and users are expected to use it in a "friendly" manner. This system is not setup for production usage, and primarily for investigating new technologies so please keep your run times short.

Software

The same software installed on the GPC is available on ARC using the same modules framework. See here for full details.

Programming Frameworks

Currently there are four programming frameworks to use: NVIDIA's CUDA framework, PGI's CUDA Fortran, PGI's implementation of OpenACC, or OpenCL.

NVIDIA K20

See


Driver Version

The current NVIDIA driver version for the K20 is 310.44


Further Info

User Codes

Please discuss and put any relevant information/problems/best practices you have encountered when using/developing for CUDA and/or OpenCL