Abstract: A temporal profiling framework useful for dynamic optimization with hot data stream prefetching provides profiling of longer bursts and lower overhead. For profiling longer bursts, the framework employs a profiling phase counter, as well as a checking phase counter, to control transitions to and from instrumented code for sampling bursts of a program execution trace. The temporal profiling framework further intelligently eliminates some checks at procedure entries and loop back-edges, while still avoiding unbounded execution without executing checks for transition to and from instrumented code. Fast hot data stream detection analyzes a grammar of a profiled data reference sequence, calculating a heat metric for recurring subsequences based on length and number of unique occurrences outside of other hot data streams in the sequence with sufficiently low-overhead to permit use in a dynamic optimization framework.

Abstract: A system and method for analyzing data accesses to determine data accessing patterns is provided. Data address accesses are traced and transformed into Whole Program Data Accesses (WPDAs). WPDAs may then be used to discover higher-level data abstractions, such as hot data blocks. Hot data blocks provide information related to sequences of data addresses that are repeatedly accessed together. Hot data blocks may then be used to improve program performance.