Speculative Parallelization in Decoupled Look-ahead Architectures

نویسندگان

  • Alok Garg
  • Raj Parihar
  • Michael C. Huang
چکیده

One well known approach to mitigate the impact of branch mispredictions and cache misses is to enable deep lookahead so as to overlap instruction and data supply with instruction processing. A continuous look-ahead process which uses separate thread of control on another hardware contexts is one such approach which we call decoupled look-ahead [1], [2]. However, in such look-ahead schemes, look-ahead thread can often become the performance bottleneck. In this work, we explore speculative parallelization in a decoupled look-ahead agent. Intuitively, speculative parallelization is aptly suited to the task of speeding up look-ahead agent for two reasons. First, the program slice for look-ahead does not contain all the data dependencies embedded in the original program, providing more opportunities for parallelization. Second, the execution of the slice is only for look-ahead purposes and thus the environment is inherently more tolerant of dependence violations.

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تاریخ انتشار 2011