{"id":3955,"date":"2011-02-28T16:15:03","date_gmt":"2011-02-28T15:15:03","guid":{"rendered":"http:\/\/www.itwriting.com\/blog\/3955-nvidia-cuda-4-0-simplifies-gpu-programming-aims-for-mainstream.html"},"modified":"2011-02-28T16:15:03","modified_gmt":"2011-02-28T15:15:03","slug":"nvidia-cuda-4-0-simplifies-gpu-programming-aims-for-mainstream","status":"publish","type":"post","link":"https:\/\/www.itwriting.com\/blog\/3955-nvidia-cuda-4-0-simplifies-gpu-programming-aims-for-mainstream.html","title":{"rendered":"NVIDIA CUDA 4.0 simplifies GPU programming, aims for mainstream"},"content":{"rendered":"<p>NVIDIA has <a href=\"http:\/\/pressroom.nvidia.com\/easyir\/customrel.do?easyirid=A0D622CE9F579F09&amp;version=live&amp;releasejsp=release_157&amp;xhtml=true&amp;prid=726171\" target=\"_blank\">announced<\/a> CUDA 4.0, a major update to its C++ toolkit for general programming on the GPU. The idea is to take advantage of the many cores of NVIDIA\u2019s GPUs for speeding up tasks that may not be graphic-related.<\/p>\n<p>There are three key features:<\/p>\n<p><strong>Unified Virtual Addressing<\/strong> provides a single address space for the main system RAM and the GPU RAM, or even RAM across multiple GPUs if available. This significantly simplifies programming.<\/p>\n<p><a href=\"http:\/\/www.itwriting.com\/blog\/wp-content\/uploads\/2011\/02\/image35.png\"><img loading=\"lazy\" decoding=\"async\" style=\"background-image: none; border-bottom: 0px; border-left: 0px; padding-left: 0px; padding-right: 0px; display: inline; border-top: 0px; border-right: 0px; padding-top: 0px\" title=\"image\" border=\"0\" alt=\"image\" src=\"http:\/\/www.itwriting.com\/blog\/wp-content\/uploads\/2011\/02\/image_thumb35.png\" width=\"404\" height=\"164\" \/><\/a><\/p>\n<p><strong>GPUDIRECT 2.0<\/strong> is NVIDIA\u2019s name for peer-to-peer communication between multiple GPUs on the same computer. Instead of copying objects from one GPU, to main memory, and to a second GPU, the data can go directly.<\/p>\n<p><strong>Thrust C++ template libraries<\/strong> <a href=\"http:\/\/code.google.com\/p\/thrust\/\" target=\"_blank\">Thrust<\/a> is a CUDA library which is similar to the parallel algorithms in the C++ Standard Template Library (STL). NVIDIA claims that typical Thrust routines are 5 to 100 times faster than with STL or Intel\u2019s Threading Building Blocks. Thrust is not really new but is getting pushed to the mainstream of CUDA programming.<\/p>\n<p>Other new features include debugging (cuda-gdb) support on Mac OS X, support for new\/delete and virtual functions in C++, and improvement to multi-threading.<\/p>\n<p>The common theme of these features is to make it easier for mortals to move from general C\/C++&#160; programming to CUDA programming, and to port existing code. This is how NVIDIA sees CUDA progress:<\/p>\n<p><a href=\"http:\/\/www.itwriting.com\/blog\/wp-content\/uploads\/2011\/02\/image36.png\"><img loading=\"lazy\" decoding=\"async\" style=\"background-image: none; border-bottom: 0px; border-left: 0px; padding-left: 0px; padding-right: 0px; display: inline; border-top: 0px; border-right: 0px; padding-top: 0px\" title=\"image\" border=\"0\" alt=\"image\" src=\"http:\/\/www.itwriting.com\/blog\/wp-content\/uploads\/2011\/02\/image_thumb36.png\" width=\"404\" height=\"146\" \/><\/a><\/p>\n<p>Certainly I see increasing interest in GPU programming, and not just among super-computer researchers.<\/p>\n<p>A weakness is that CUDA only works on NVIDIA GPUs. You can use <a href=\"http:\/\/www.khronos.org\/opencl\/\" target=\"_blank\">OpenCL<\/a> for generic GPU programming but it is less advanced.<\/p>\n<p>CUDA 4.0 release candidate will be available from March 4 if you sign up for the <a href=\"http:\/\/www.nvidia.com\/paralleldeveloper\" target=\"_blank\">CUDA Registered Developer Program<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>NVIDIA has announced CUDA 4.0, a major update to its C++ toolkit for general programming on the GPU. The idea is to take advantage of the many cores of NVIDIA\u2019s GPUs for speeding up tasks that may not be graphic-related. There are three key features: Unified Virtual Addressing provides a single address space for the &hellip; <a href=\"https:\/\/www.itwriting.com\/blog\/3955-nvidia-cuda-4-0-simplifies-gpu-programming-aims-for-mainstream.html\" class=\"more-link\">Continue reading <span class=\"screen-reader-text\">NVIDIA CUDA 4.0 simplifies GPU programming, aims for mainstream<\/span> <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[80],"tags":[307,436,654],"class_list":["post-3955","post","type-post","status-publish","format-standard","hentry","category-software-development","tag-cuda-4-0","tag-gpu-computing","tag-nvidia"],"_links":{"self":[{"href":"https:\/\/www.itwriting.com\/blog\/wp-json\/wp\/v2\/posts\/3955","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.itwriting.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.itwriting.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.itwriting.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.itwriting.com\/blog\/wp-json\/wp\/v2\/comments?post=3955"}],"version-history":[{"count":0,"href":"https:\/\/www.itwriting.com\/blog\/wp-json\/wp\/v2\/posts\/3955\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.itwriting.com\/blog\/wp-json\/wp\/v2\/media?parent=3955"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.itwriting.com\/blog\/wp-json\/wp\/v2\/categories?post=3955"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.itwriting.com\/blog\/wp-json\/wp\/v2\/tags?post=3955"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}