Slackness-Based Co-Scheduling Hardware and Software Pipelines with Multiple Latency Sequences
TL;DRAbstract
Pipelining is by far one of the most used approaches for achieving higher instruction level parallelism. To exploit this parallelism, various scheduling algorithms were introduced. Co-scheduling hardware and software pipelines is a new approach for scheduling operations from different iterations of a loop (software pipelining) and reconfiguring the hardware pipelines to achieve higher instruction level parallelism. This scheduling algorithm is based on the slackness of the operation. In this paper, we extend the original co-scheduling algorithm and study the effect of the initial slackness of the operation. We introduce a method to select the most suitable latency sequence among the available latency sequences. Furthermore, we modify the selection criterion which is used to select an instruction for scheduling. The new criterion performs better than the original one. The new scheduling algorithm is implemented and compared with the original co-scheduling approach. We test the algorithm
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Pipelining is by far one of the most used approaches for achieving higher instruction level parallelism. To exploit this parallelism, various scheduling algorithms were introduced. Co-scheduling hardware and software pipelines is a new approach for scheduling operations from different iterations of a loop (software pipelining) and reconfiguring the hardware pipelines to achieve higher instruction level parallelism. This scheduling algorithm is based on the slackness of the operation. In this paper, we extend the original co-scheduling algorithm and study the effect of the initial slackness of the operation. We introduce a method to select the most suitable latency sequence among the available latency sequences. Furthermore, we modify the selection criterion which is used to select an instruction for scheduling. The new criterion performs better than the original one. The new scheduling algorithm is implemented and compared with the original co-scheduling approach. We test the algorithm
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