Simple, Parallel, High-Performance Virtual Machines for Extreme Computations

TL;DR

This paper presents a high-performance virtual machine designed for evaluating large expressions and complex computations in high-energy physics, enabling faster and more scalable calculations than traditional methods.

Contribution

The paper introduces a novel VM implementation in fast languages like Fortran or C that efficiently computes tree-level cross sections and facilitates parallel processing for high multiplicity calculations.

Findings

VM can outperform native code for high multiplicities

Parallel computation simplifies phase space evaluations

Avoids lengthy compile and link steps for large codebases

Abstract

We introduce a high-performance virtual machine (VM) written in a numerically fast language like Fortran or C to evaluate very large expressions. We discuss the general concept of how to perform computations in terms of a VM and present specifically a VM that is able to compute tree-level cross sections for any number of external legs, given the corresponding byte code from the optimal matrix element generator, O'Mega. Furthermore, this approach allows to formulate the parallel computation of a single phase space point in a simple and obvious way. We analyze hereby the scaling behaviour with multiple threads as well as the benefits and drawbacks that are introduced with this method. Our implementation of a VM can run faster than the corresponding native, compiled code for certain processes and compilers, especially for very high multiplicities, and has in general runtimes in the same order of magnitude. By avoiding the tedious compile and link steps, which may fail for source code files of gigabyte sizes, new processes or complex higher order corrections that are currently out of reach could be evaluated with a VM given enough computing power.