In this video from PyData NYC 2012, Andreas Klöckner from New York University presents a brief introduction to GPU programming with Python, including run-time code generation and use of high-level tools like PyCUDA, PyOpenCL, and Loo.py. Related posts:Slidecast: SPM.Python Expoits Parallelism with Fault ToleranceTerrel on Getting Started With Python in...

This week Bright Computing announced that Tsinghua University in China is using the company’s software to manage its Hadoop-based cluster for climate modeling. The university selected Bright Cluster Manager because it provided a powerful solution for deploying, testing, provisioning, monitoring and managing its cluster while minimizing staffing requirements. We needed a solution that would provide deep insights and better visibility into every aspect of our cluster. Bright’s highly intuitive interface gives us a complete view, including the ability to drill...

Intel’s James Reinders writes that the company is now offering a set of free Intel C++ parallel programming tools (and discounts on Fortran tools) for students. These are serious tools to achieving high performance results with C++ programming through optimization, analysis and support for the latest standards. These are interesting...

Over at Enterprise Storage Forum, Henry Newman from Instrumental is out with his Ten Storage Predictions for 2012, and his last one is more of plea for reason. The industry really needs more than POSIX (open/fopen, read/fread,write/fwrite) and more than simple REST put/get interfaces for data in the future. Neither has the richness...