MoreFit: A More Optimised, Rapid and Efficient Fit

TL;DR

MoreFit is a new software tool that significantly improves the speed and efficiency of unbinned maximum likelihood fits in particle physics by leveraging parallelism, just-in-time compilation, and open standards for heterogeneous computing.

Contribution

It introduces a novel, highly optimized fitting framework that employs automatic optimization techniques and supports multiple hardware platforms through open standards.

Findings

MoreFit outperforms existing fitting frameworks in speed.

It effectively utilizes GPUs and CPUs with SIMD and multithreading.

Benchmark results show promising performance improvements.

Abstract

Parameter estimation via unbinned maximum likelihood fits is a central technique in particle physics. This article introduces MoreFit, which aims to provide a more optimised, rapid and efficient fitting solution for unbinned maximum likelihood fits. MoreFit is developed with a focus on parallelism and relies on computation graphs that are compiled just-in-time. Several novel automatic optimisation techniques are employed on the computation graphs that significantly increase performance compared to conventional approaches. MoreFit can make efficient use of a wide range of heterogeneous platforms through its compute backends that rely on open standards. It provides an OpenCL backend for execution on GPUs of all major vendors, and a backend based on LLVM and Clang for single- or multithreaded execution on CPUs, which in addition allows for SIMD vectorisation. MoreFit is benchmarked against several other fitting frameworks and shows very promising performance, illustrating the power of the approach.