Today, the multi-core processor has occupied more and more market shares, and the programming personnel also must face the collision brought by the revolution of multi-core processor. Semiconductor scaling limits and associated power and thermal challenges limit performance growth for single-core microprocessors. This reason leads many microprocessor vendors to turn instead to multi-core chip organizations. So programmer or compiler explicitly parallelize the software is the key for enhance the performance on multi-core chip. At the same time, parallel processing is not only the opportunity but also a challenge. The programmer or compiler explicitly parallelize the software is the key for enhance the performance on multi-core chip. In this paper, what we want to know is there any effective way that can reduce our time on rewrite or can automatically parallel the program for multi-processing purpose and do speedup the processing. We discussed some tools that can automatically generate OpenMP directives from serial C\/C++ codes, and compare them with each other include normal C\/C++ code, and run on general computer and embedded system. Also we compared some tools that are specifically designed to extract the most of data parallelism from C and FORTRAN kernels and translate them into NVIDIA CUDA or OpenCL to know how mush fast after use them.<\/p>\n","protected":false},"excerpt":{"rendered":"
Today, the multi-core processor has occupied more and more market shares, and the programming personnel also must face the collision brought by the revolution of multi-core processor. Semiconductor scaling limits and associated power and thermal challenges limit performance growth for single-core microprocessors. This reason leads many microprocessor vendors to turn instead to multi-core chip organizations. […]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[11,89,90,3],"tags":[215,955,1782,14,263,989,20,1793,252,67],"class_list":["post-5054","post","type-post","status-publish","format-standard","hentry","category-computer-science","category-nvidia-cuda","category-opencl","category-paper","tag-code-generation","tag-compilers","tag-computer-science","tag-cuda","tag-data-parallelism","tag-fortran","tag-nvidia","tag-opencl","tag-openmp","tag-performance"],"views":2007,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5054","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=5054"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5054\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5054"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5054"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5054"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}