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NVIDIA CUDA Toolkit 3.1 |
The CUDA Toolkit 3.1 packs the following updates and additions: - GPUDirect gives 3rd party devices direct access to CUDA Memory - Support for 16-way concurrency allows up to 16 different kernels to run at the same time on Fermi architecture GPUs - Runtime / Driver interoperability enables applications to mix-n-match use of the CUDA Driver API with CUDA C Runtime and math libraries via buffer sharing and context migration - New language features added to CUDA C / C++: Support for printf() in device code Support for function pointers and recursion make it easier to port many existing algorithms to Fermi GPUs - Unified Visual Profiler now supports both CUDA C/C++ and OpenCL, and now includes support for CUDA Driver API tracing - Math Libraries Performance Improvements, including: Improved performance of selected transcendental functions from the log, pow, erf, and gamma families Significant improvements in double-precision FFT performance on Fermi-architecture GPUs for 2^n transform sizes Streaming API now supported in CUBLAS for overlapping copy and compute operations CUFFT Real-to-complex (R2C) and complex-to-real (C2R) optimizations for 2^n data sizes Improved performance for GEMV and SYMV subroutines in CUBLAS Optimized double-precision implementations of divide and reciprocal routines for the Fermi architecture - New and updated SDK code samples demonstrating how to use: Function pointers in CUDA C/C++ kernels OpenCL / Direct3D buffer sharing Hidden Markov Model in OpenCL Microsoft Excel GPGPU example showing how to run an Excel function on the GPU |
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