CUDA Toolkit 3.2 RC (September 2010) 公开下载

Edison

Release Highlights

New and Improved CUDA Libraries

• CUSPARSE, a new library of GPU-accelerated sparse matrix routines for sparse/sparse and dense/sparse operations
• CURAND, a new library of GPU-accelerated random number generation (RNG) routines, supporting Sobol quasi-random and XORWOW pseudo-random routines for in both host and device code
• CUFFT performance tuned for radix-3, -5, and -7 transform sizes on Fermi architecture GPUs
• CUBLAS performance improved 50% to 300% on Fermi architecture GPUs, for matrix multiplication of all datatypes and transpose variations
• H.264 encode/decode libraries that were previously available in the GPU Computing SDK are now part of the CUDA Toolkit
  

CUDA Driver & CUDA C Runtime

• Support for new 6GB Quadro and TeslPro-Aducts
• Support for debugging GPUs with more than 4GB device memory.
• Integrated Tesla Compute Cluster (TCC) support in standard Windows driver packages
  

Development Tools

• Multi-GPU debugging support for both cuda-gdb and Parallel Nsight
• Added cuda-memcheck support for Fermi architecture GPUs
• NVCC support for Intel C Compiler (ICC) v11.1 on 64-bit Linux distros
  

Miscellaneous

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

New GPU Computing SDK Code Samples

• Several code samples demonstrating how to use the new CURAND library, including MonteCarloCURAND, EstimatePiInlineP, EstimatePiInlineQ, EstimatePiP, EstimatePiQ, and SingleAsianOptionP
• Conjugate Gradient Solver, demonstrating the use of CUBLAS and CUSPARSE together
• 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 an cuprintf in compute kernels
• Bilateral Filter, an edge-preserving non-linear smoothing filter for image recovery and denoising that is 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
  

http://developer.nvidia.com/object/cuda_3_2_toolkit_rc.html

yyzjp

Support for debugging GPUs with more than 4GB device memory
超过4GB显存的显卡在哪里？

gzpony

Support for debugging GPUs with more than 4GB device memory
超过4GB显存的显卡在哪里？
yyzjp 发表于 2010-9-18 15:36

专业卡里。
上次有人贴的新闻里面，貌似见过6G显存的型号的

drhuangyt

开始有稀疏矩阵求解、随机数生成、快速傅利叶变换、三角分解矩阵运算库了，不知道跟MKL比效率如何

jocover

发现 2D_MAX_HEIGHT 变32768了，原来是8192

  CL_DEVICE_IMAGE <dim>        
                    2D_MAX_WIDTH     4096
                    2D_MAX_HEIGHT     32768
                    3D_MAX_WIDTH     2048
                    3D_MAX_HEIGHT     2048
                    3D_MAX_DEPTH     2048

yyzjp

稍微关心点新闻应该清楚Fermi核心的Quadro FX6000用的就是6G的GDDR5显存
未来的水世界 发表于 2010-9-18 18:37

    sorry ,我忘记了专业卡