Nvidia has just announced the release of version 3.0 of the CUDA toolkit. One of the new features for this release is, of course, that it supports the new Fermi chip that is slated to be released real soon now. Other features include support for ECC memory, and optimized double precision support.
There’s been a lot of anticipation about how the Fermi architecture can help accelerate research. The release of the 3.0 toolkit means that the scientific community is a step closer to realizing some of these performance gains. We talked to Professor Richard Brower, U.S. Software Coordinator for USQCD, Boston University Physics and Electrical Engineering Departments, about what the new toolkit means for his research in quantum chromodynamics (QCD), an area of particle physics.
“QCD codes need all the compute cycles they can get and we’re really excited about the results we’re getting by using GPUs – we’ve already reduced the cost of our calculations by a factor of 5,” Professor Bower said, adding that features in the new CUDA Toolkit that are essential for high performance computing – like GPU acceleration for more complex linear algebra routines – are going to help advance his QCD research.
The new toolkit lets developers take advantage of innovations in the Fermi architecture that make these new GPUs exceptionally well suited for scientific applications.
Some of the new features include:
- Support for new GPUs based on Fermi architecture – including ECC, optimized double precision, support for linear algebra libraries such as BLAS and LAPACK, the CUDA-GDB debugger and Visual Profiler
- C++ support – delivering improved productivity with class and template inheritance
- GPGPU/Graphics interoperability – delivering Direct3D 9, 10 and 11 and OpenGL for both CUDA and OpenCL
- Improved developer tools for Linux – including the new CUDA Memory Checker that reports misalignment and out-of-bounds errors
- Tesla Compute Cluster (TCC) – improving performance and cluster management
