Title :
High performance table-based architecture for parallel CRC calculation
Author :
Yuanhong Huo ; Xiaoyang Li ; Wei Wang ; Dake Liu
Author_Institution :
Sch. of Comput. Sci. & Technol., Beijing Inst. of Technol., Beijing, China
Abstract :
A high performance table-based architecture implementation for CRC (cyclic redundancy check) algorithms is proposed. The architecture is designed based on a highly parallel CRC algorithm. The algorithm first divides a given message with any length into bytes. Then it performs CRC computation using lookup tables among the divided bytes in parallel. At last, the results are XORed to obtain the CRC value of the given message. The algorithm is table-based and can accelerate different CRC algorithms. Based on the algorithm, the architecture is designed to accelerate CRC algorithms with high parallelism and flexibility. The architecture is configurable and can support CRC algorithms such as CRC32, CRC24, CRC-CCITT, CRC16, CRC8. CRC value of 128-bit input data can be generated in one cycle. Our method also allows calculation over data that is less than 128-bit wide without increasing hardware cost. With 128-bit input each clock cycle, the throughput of the proposed architecture reaches up to 100 Gbps by utilizing 16 KB SRAM (Static Random Access Memory) with about 12% area reduction compared with previous work.
Keywords :
SRAM chips; cyclic redundancy check codes; parallel algorithms; parallel architectures; table lookup; CRC computation; CRC-CCITT; CRC16; CRC24; CRC32; CRC8; SRAM; clock cycle; cyclic redundancy check; high performance table-based architecture; lookup tables; parallel CRC algorithm; parallel CRC calculation; static random access memory; Acceleration; Algorithm design and analysis; Computer architecture; Generators; Hardware; Polynomials; Throughput; CRC generation; parallel algorithm; parallel architecture;
Conference_Titel :
Local and Metropolitan Area Networks (LANMAN), 2015 IEEE International Workshop on
Conference_Location :
Beijing
DOI :
10.1109/LANMAN.2015.7114717