Memoization is the technique of saving the results of computations so that future executions can be omitted when the same inputs repeat. Recent work showed that memoization can be applied to dynamically linked pure functions using a load-time technique and results were encouraging for the demonstrated transcendental functions. A restriction of the proposed framework was that memoization was restricted only to dynamically linked functions and the functions must be determined beforehand. In this work, we propose function memoization using a compile-time technique thus extending the scope of memoization to user defined functions as well as making it transparently applicable to any dynamically linked functions. Our compile-time technique allows static linking of memoization code and this increases the benefit due to memoization by leveraging the inlining capability for the memoization wrapper. Our compile-time analysis can also handle functions with pointer parameters, and we handle constants more efficiently. Instruction set support can also be considered, and we propose associated hardware leading to additional performance gain.
Sun 5 FebDisplayed time zone: Saskatchewan, Central America change
13:30 - 15:10 | |||
13:30 25mTalk | Compile-Time Function Memoization Research Papers DOI | ||
13:55 25mTalk | One Compiler: Deoptimization to Optimized Code Research Papers Christian Wimmer , Vojin Jovanovic Oracle Labs, Erik Eckstein Oracle Labs, USA, Thomas Wuerthinger Oracle Labs DOI | ||
14:20 25mTalk | Static Optimization in PHP 7 Research Papers Nikita Popov TU Berlin, Germany, Biagio Cosenza TU Berlin, Germany, Ben Juurlink TU Berlin, Germany, Dmitry Stogov Zend Technologies, Russia DOI | ||
14:45 25mTalk | From Functional Programs to Pipelined Dataflow Circuits Research Papers DOI |