Conjugate Gradient Solver, demonstrating the use of CUBLAS and CUSPARSE in the same application.

Several code samples demonstrating how to use the new CURAND library, including MonteCarloCURAND, EstimatePiInlineP, EstimatePiInlineQ, EstimatePiP, EstimatePiQ, SingleAsianOptionP, and randomFog.

New NVIDIA System Management Interface (nvidia-smi) support for reporting % GPU busy, and several GPU performance counters.

Support for memory management using malloc() and free() in CUDA C compute kernels.

Support for debugging GPUs with more than 4GB device memory.

NVCC support for Intel C Compiler (ICC) v11.1 on 64-bit Linux distros.

Expanded cuda-memcheck support for all Fermi architecture GPUs.

Multi-GPU debugging support for both cuda-gdb and Parallel Nsight.

New support for enabling high performance Tesla Compute Cluster (TCC) mode on Tesla GPUs in Windows desktop workstations.

Support for new 6GB Quadro and Tesla products.

H.264 encode/decode libraries now included in the CUDA Toolkit.

New CURAND library of GPU-accelerated random number generation (RNG) routines, supporting Sobol quasi-random and XORWOW pseudo-random routines at 10x to 20x faster than similar routines in MKL.

New CUSPARSE library of GPU-accelerated sparse matrix routines for sparse/sparse and dense/sparse operations delivers 5x to 30x faster performance than MKL.

CUFFT performance tuned for radix-3, -5, and -7 transform sizes on Fermi architecture GPUs, now 2x to 10x faster than MKL.

CUBLAS performance improved 50% to 300% on Fermi architecture GPUs, for matrix multiplication of all datatypes and transpose variations.

Release Highlights New and Improved CUDA Libraries Individual code samples from the SDK are also available.

Nvidia 462.59