Intercepting Functions for Memoization

ISBN-13: 9783841666123 / Angielski / Miękka / 2017 / 132 str.

Arjun Suresh

Opis

We have proposed mechanisms to implement function memoization at a software level as part of our effort to improve sequential code performance. We have analyzed the potential of function memoization on applications and its performance gain on current architectures. We have proposed three schemes - a simple load time approach which works for any dynamically linked function, a compile time approach using LLVM framework which can enable memoization for any program function and also a hardware proposal for doing memoization in hardware and its potential benefits. Demonstration of the link time approach with transcendental functions showed that memoization is applicable and gives good benefit even under modern architectures and compilers (with the restriction that it can be applied only for dynamically linked functions). Our compile time approach extends the scope of memoization and also increases the benefit due to memoization. This works for both user defined functions as well as library functions. It can handle certain kind of non pure functions like those functions with pointer arguments and global variable usage.

O autorze

I'm currently working on certain extensions of GATE Overflow which is a complete exam preparation package for GATE preparation for Computer Science stream. Before this I did my post doctoral research at The Ohio State University on high-performance GPU implementations of Tensor algebra operations.