# A Technique for Finding Optimal Program Launch Parameters Targeting Manycore Accelerators

## TL;DR

This paper introduces a novel static-to-dynamic technique for optimizing program parameters, especially for GPU kernels on manycore accelerators, by building a program that predicts optimal settings for improved performance.

## Contribution

The paper presents a new method to automatically generate a program that dynamically finds optimal parameters for multithreaded programs targeting manycore accelerators.

## Key findings

- Successfully applied to GPU kernels using MWP-CWP model
- Improves performance by optimizing program parameters dynamically
- Applicable to parallel programs on manycore architectures

## Abstract

In this paper, we present a new technique to dynamically determine the values of program parameters in order to optimize the performance of a multithreaded program P. To be precise, we describe a novel technique to statically build another program, say, R, that can dynamically determine the optimal values of program parameters to yield the best program performance for P given values for its data and hardware parameters. While this technique can be applied to parallel programs in general, we are particularly interested in programs targeting manycore accelerators. Our technique has successfully been employed for GPU kernels using the MWP-CWP performance model for CUDA.