New and Improved CUDA Libraries

• CUBLAS performance improved 50% to 300% on Fermi architecture GPUs, for matrix multiplication of all datatypes and transpose variations
• CUFFT performance tuned for radix-3, -5, and -7 transform sizes on Fermi architecture GPUs, now 2x to 10x faster than 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
• 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
• H.264 encode/decode libraries now included in the CUDA Toolkit
• CUDA Driver & CUDA C Runtime
• Support for new 6GB Quadro and Tesla products
• New support for enabling high performance Tesla Compute Cluster (TCC) mode on Tesla GPUs in Windows desktop workstations

• Multi-GPU debugging support for both cuda-gdb and Parallel Nsight
• Expanded cuda-memcheck support for all Fermi architecture GPUs
• NVCC support for Intel C Compiler (ICC) v11.1 on 64-bit Linux distros
• Support for debugging GPUs with more than 4GB device memory

• Support for memory management using malloc() and free() in CUDA C compute kernels
• New NVIDIA System Management Interface (nvidia-smi) support for reporting % GPU busy, and several GPU performance counters

• Several code samples demonstrating how to use the new CURAND library, including MonteCarloCURAND, EstimatePiInlineP, EstimatePiInlineQ, EstimatePiP, EstimatePiQ, SingleAsianOptionP, and randomFog
• Conjugate Gradient Solver, demonstrating the use of CUBLAS and CUSPARSE in the same application
• Function Pointers, a sample that shows how to use function pointers to implement the Sobel Edge Detection filter for 8-bit monochrome images
• Interval Computing, demonstrating the use of interval arithmetic operators using C++ templates and recursion
• Simple Printf, demonstrating best practices for using both printf and cuprintf in compute kernels
• Bilateral Filter, an edge-preserving non-linear smoothing filter for image recovery and denoising implemented in CUDA C with OpenGL rendering
• SLI with Direct3D Texture, a simple example demonstrating the use of SLI and Direct3D interoperability with CUDA C
• cudaEncode, showing how to use the NVIDIA H.264 Encoding Library using YUV frames as input
• Vflocking Direct3D/CUDA, which simulates and visualizes the flocking behavior of birds in flight
• simpleSurfaceWrite, demonstrating how CUDA kernels can write to 2D surfaces on Fermi GPUs

New and Improved CUDA Libraries

• CUBLAS performance improved 50% to 300% on Fermi architecture GPUs, for matrix multiplication of all datatypes and transpose variations
• CUFFT performance tuned for radix-3, -5, and -7 transform sizes on Fermi architecture GPUs, now 2x to 10x faster than MKL
• New CUSPARSE library of GPU-accelerated sparse matrix routines for more...