Algorithm-level recomputing with shifted operands-a register transfer level concurrent error detection technique

摘要

This paper presents Algorithm-level REcomputing with Shifted Operands (ARESO), which is a new register transfer (RT) level time redundancy-based concurrent error detection (CED) technique. In REcomputing with Shifted Operands (RESO), operations (additions, subtractions, etc.) are carried out twice-once on the basic input and once on the shifted input. Results from these two operations are compared to detect an error. Although using RESO operators in RT-level designs is straightforward, it entails time and area overhead. In contrast, ARESO does not use specialized RESO operators. In ARESO, an algorithm is carried out twice-once on the basic input and once on the shifted input. Results from these two algorithm-level instantiations are compared to detect an error. By operating at the algorithm level, ARESO exploits RT-level scheduling, pipelining, operator chaining, and multicycling to incorporate user-specified error detection latencies. ARESO supports hardware versus performance versus error detection latency tradeoffs. The authors validated ARESO on practical design examples using the Synopsys Behavior Compiler (BC). An industry standard behavioral synthesis system.