{"title":"无冲突矢量有序就地基-r信念传播极化码译码算法","authors":"Arvid B. van den Brink, M. Bekooij","doi":"10.1145/3390525.3390539","DOIUrl":null,"url":null,"abstract":"A vectorized belief propagation polar code decoder is desirable because of the potentially high throughput and the ability of integration in processors that perform vectorized processing and access wide memory words. However, current state-of-the-art belief propagation polar code decoder algorithms do not perform vector processing and store intermediate results in non consecutive memory locations. Also the current state-of-the-art belief propagation polar code decoders require separate memories to store left and right bound intermediate results. In this paper we propose a vectorized in-order in-place belief propagation polar code decoder algorithm where all stages access vectorized data from memory. This results in a high throughput because vectors of elements can be fetched from and stored in memory in each clock cycle. Our algorithm also accommodates for per stage in-place computations which halves the required internal memory. Furthermore, the algorithm has a regular memory addresses access pattern. Conflict free vectorized memory access is achieved by making use of transpose operations on small groups of intermediate results. The use of the transpose operations also results in that both input and output results are placed on subsequent locations in memory.","PeriodicalId":201179,"journal":{"name":"Proceedings of the 2020 8th International Conference on Communications and Broadband Networking","volume":"114 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Conflict-Free Vectorized In-order In-place Radix-r Belief Propagation Polar Code Decoder Algorithm\",\"authors\":\"Arvid B. van den Brink, M. Bekooij\",\"doi\":\"10.1145/3390525.3390539\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A vectorized belief propagation polar code decoder is desirable because of the potentially high throughput and the ability of integration in processors that perform vectorized processing and access wide memory words. However, current state-of-the-art belief propagation polar code decoder algorithms do not perform vector processing and store intermediate results in non consecutive memory locations. Also the current state-of-the-art belief propagation polar code decoders require separate memories to store left and right bound intermediate results. In this paper we propose a vectorized in-order in-place belief propagation polar code decoder algorithm where all stages access vectorized data from memory. This results in a high throughput because vectors of elements can be fetched from and stored in memory in each clock cycle. Our algorithm also accommodates for per stage in-place computations which halves the required internal memory. Furthermore, the algorithm has a regular memory addresses access pattern. Conflict free vectorized memory access is achieved by making use of transpose operations on small groups of intermediate results. The use of the transpose operations also results in that both input and output results are placed on subsequent locations in memory.\",\"PeriodicalId\":201179,\"journal\":{\"name\":\"Proceedings of the 2020 8th International Conference on Communications and Broadband Networking\",\"volume\":\"114 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2020 8th International Conference on Communications and Broadband Networking\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3390525.3390539\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 8th International Conference on Communications and Broadband Networking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3390525.3390539","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A vectorized belief propagation polar code decoder is desirable because of the potentially high throughput and the ability of integration in processors that perform vectorized processing and access wide memory words. However, current state-of-the-art belief propagation polar code decoder algorithms do not perform vector processing and store intermediate results in non consecutive memory locations. Also the current state-of-the-art belief propagation polar code decoders require separate memories to store left and right bound intermediate results. In this paper we propose a vectorized in-order in-place belief propagation polar code decoder algorithm where all stages access vectorized data from memory. This results in a high throughput because vectors of elements can be fetched from and stored in memory in each clock cycle. Our algorithm also accommodates for per stage in-place computations which halves the required internal memory. Furthermore, the algorithm has a regular memory addresses access pattern. Conflict free vectorized memory access is achieved by making use of transpose operations on small groups of intermediate results. The use of the transpose operations also results in that both input and output results are placed on subsequent locations in memory.