Using GPUs with #golang (2014-05-07)
A nice presentation about how to use the Go programming language (#golang) with CUDA (from FOSDEM 2014): Scientific GPU Computing with Google's Go Language
Go 1.1 Released (2013-05-06)
The new version keeps compatiblity and adds several language and library changes. Some of them are method values, terminating statements, the size of int on lx-amd64 (now 64 bit), as well as heap size changes for large applications. The complete list is here.
Nvidia's Hyper Q Helps Applications to Share One GPU (2013-04-30)
This interesting article describes how the Hyper-Q scheduler from Nvidia is used in order to run multiple MPI processes concurrently on one GPU. Using the alarm state (in order to exclude fully loaded hosts/GPUs for new jobs in the Grid Engine job list/queue) and load values/load thresholds from the GPU and the CPUs Grid Engine should be able to handle this scenario well.
Management and Monitoring of GPU Clusters (2013-03-26)
This presentation from the HPC Advisory Council Conference 2013 gives an introduction about management and monitoring of GPUs.
Why NUMA Matters and Univa Grid Engine Supports CPU and Memory Affinity (2013-02-28)
Benjamin Cumming from the Swiss National Supercomputing Center explains in this video core binding and memory affinity on NUMA machines in general.
Intel Launches own Hadoop Distribution (2013-02-27)
Intel deploys now its own Hadoop. More information you can find here, or here. Intel hosts its source code at github. For official Intel information go to the Intel Hadoop page.
Intel also approaches security questions with Project Rhino: "As Hadoop extends into new markets and sees new use cases with security and compliance challenges, the benefits of processing sensitive and legally protected data with all Hadoop projects and HBase must be coupled with protection for private information that limits performance impact. Project Rhino is our open source effort to enhance the existing data protection capabilities of the Hadoop ecosystem to address these challenges, and contribute the code back to Apache."