Read-after-read memory dependence prediction

We identify that typical programs which exhibit highly regular read-after-read (RAR) memory dependence streams. We exploit this regularity by introducing read-after-read (RAR) memory dependence prediction. We also present two RAR memory dependence prediction-based memory latency reduction techniques. In the first technique, a load can obtain a value by simply naming a preceding load with which a RAR dependence is predicted. The second technique speculatively converts a series of LOAD₁-USE₁,…,LOAD_N-USE _N chains into a single LOAD₁-USE₁…USE_N producer/consumer graph. Our techniques can be implemented as surgical extensions to the recently proposed read-after-write (RAW) dependence prediction based speculative memory cloaking and speculative memory bypassing. On average, our techniques provide correct values for an additional 20% (integer codes) and 30% (floating-point codes) of all loads. Moreover, a combined RAW- and RAR-based cloaking/bypassing mechanism improves performance by 6.44% (integer) and 4.66% (floating-point) even when naive memory dependence speculation is used. The original RAW-based cloaking/bypassing mechanism yields improvements of 4.28% (integer) and 3.20% (floating-point)