Compressing Extended Program Traces Using Value Predictors

Trace files record the execution behavior of programs for future analysis. Unfortunately, nontrivial program traces tend to be very large and have to be compressed. While good compression schemes exist for traces that capture only the PCs of the executed instructions, these schemes can be ineffective on extended traces that include important additional information such as register values or effective addresses. Our novel, value-prediction-based approach compresses extended traces up to 22.8 times better and about two and a half times as well on average. In addition to the higher compression rate, our lossless single-pass algorithm has a fixed memory requirement and compresses traces faster than other algorithms. It achieves compression rates of up to 6170. This paper describes the design of our compression method and illustrates how value predictors can be used to effectively compress extended program traces

Summarizing multiprocessor program execution with versatile, microarchitecture-independent snapshots

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 131-137).Computer architects rely heavily on software simulation to evaluate, refine, and validate new designs before they are implemented. However, simulation time continues to increase as computers become more complex and multicore designs become more common. This thesis investigates software structures and algorithms for quickly simulating modern cache-coherent multiprocessors by amortizing the time spent to simulate the memory system and branch predictors. The Memory Timestamp Record (MTR) summarizes the directory and cache state of a multiprocessor system in a compact data structure. A single MTR snapshot is versatile enough to reconstruct the microarchitectural state resulting from various coherence protocols and cache organizations. The MTR may be quickly updated by each simulated processor during a fast-forwarding phase and optionally stored off-line for reuse. To fill large branch prediction tables, we introduce Branch Predictor-based Compression (BPC) which compactly stores a branch trace so that it may be used to fill in any branch predictor structure. An entire BPC trace requires less space than single discrete predictor snapshots, and it may be decompressed 3-6x faster than performing functional simulation.by Kenneth C. Barr.Ph.D