Abstract. Software Transactional Memory (STM) compilers commonly instrument memory accesses by transforming them into calls to STM library functions. Done naïvely, this instrumentation imposes a large overhead, slowing down the transaction execution. Many compiler optimizations have been proposed in an attempt to lower this overhead. In this paper we attempt to drive the STM overhead lower by discovering sources of sub-optimal instrumentation, and providing optimizations to eliminate them. The sources are: (1) redundant reads of memory locations which have been read before, (2) redundant writes to memory locations which will be subsequently written to, (3) redundant writeset lookups of memory locations which have not been written to, and (4) redundant writeset record-keeping for memory locations which will not be read. We describe how static analysis and code motion algorithms can detect these sources, and enable compile-time optimizations that signicantly reduce the instrumentation overhead in many common cases. We implement the optimizations over a TL2 Java-based STM system, and demonstrate the eectiveness of the optimizations on various benchmarks, measuring up to 29-50% speedup in a single-threaded run, and up to 19% increased throughput in a 32-threads run.
REF propose static analysis and code motion to decrease the number of memory accesses.
Lowering STM overhead with static analysis
In LCPC
Computer Science