Prediction and trace compression of data access addresses through nested loop recognition
Proceedings of the 6th annual IEEE/ACM international symposium on Code generation and optimization
Scalable Communication Trace Compression
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
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Program traces are commonly used for purposes such as profiling, processor simulation, and program slicing. Uncompressed, these traces are often too large to exist on disk. Although existing trace compression algorithms achieve high compression rates, they sacrifice the accessibility of uncompressed traces; typical compressed traces must be traversed linearly to reach a desired position in the stream. This paper describes seekable compressed traces that allow arbitrary positioning in the compressed data stream. Furthermore, we enhance existing value prediction based techniques to achieve higher compression rates, particularly for difficult-to-compress traces. Our base algorithm achieves a harmonic mean compression rate for SPEC2000 memory address traces that is 3.47 times better than existing methods. We introduce the concept of seekpoints that enable fast seeking to positions evenly distributed throughout a compressed trace. Adding seekpoints enables rapid sampling and backwards traversal of compressed traces. At a granularity of every 10M instructions, seekpoints only increase trace sizes by an average factor of 2.65.