Section: New Software and Platforms

If-memo

Keyword: Performance

Scientific Description: We propose a linker based technique for enabling software memorizing of any dynamically linked pure function by function interception and we illustrate our framework using a set of computationally expensive pure functions - the transcendental functions. Our technique does not need the availability of source code and thus can even be applied to commercial applications as well as applications with legacy codes. As far as users are concerned, enabling memoization is as simple as setting an environment variable. Our framework does not make any specific assumptions about the underlying architecture or compiler too-chains, and can work with a variety of current architectures.

• Participants: Arjun Suresh and Erven Rohou

• Contact: Erven Rohou

• URL: https://team.inria.fr/alf/software/if-memo/