Nonbinary Low-Density Parity-Check (LDPC) codes are a class of error-correcting codes constructed over the Galois field GF(q) for q > 2. As extensions of binary LDPC codes, nonbinary LDPC codes can provide better error-correcting performance when the code length is short or moderate, but at a cost of higher decoding complexity. This paper proposes a massively parallel implementation of a nonbinary LDPC decoding accelerator based on a graphics processing unit (GPU) to achieve both great flexibility and scalability. The implementation maps the Min-Max decoding algorithm to GPU’s massively parallel architecture. We highlight the methodology to partition the decoding task to a heterogeneous platform consisting of the CPU and GPU. The experimental results show that our GPUbased implementation can achieve high throughput while still providing great flexibility and scalability.<\/p>\n","protected":false},"excerpt":{"rendered":"
Nonbinary Low-Density Parity-Check (LDPC) codes are a class of error-correcting codes constructed over the Galois field GF(q) for q > 2. As extensions of binary LDPC codes, nonbinary LDPC codes can provide better error-correcting performance when the code length is short or moderate, but at a cost of higher decoding complexity. This paper proposes a […]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_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}},"categories":[36,11,89,3],"tags":[1787,1782,14,452,20,953,797],"class_list":["post-8581","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-computer-science","category-nvidia-cuda","category-paper","tag-algorithms","tag-computer-science","tag-cuda","tag-heterogeneous-systems","tag-nvidia","tag-nvidia-geforce-gtx-470","tag-parity-check-codes"],"views":2589,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8581","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=8581"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/8581\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=8581"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=8581"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=8581"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}