Graph500 from OCaml-Multicore Perspective
Shubhendra Pal Singhal

TL;DR
This paper presents an implementation and performance analysis of Graph500 benchmarks using OCaml-Multicore, focusing on graph algorithms like construction, BFS, and shortest path, with insights into data structures, algorithms, and performance challenges.
Contribution
It provides a detailed OCaml-based implementation of Graph500 benchmarks, including algorithm choices, data structures, and performance analysis, highlighting challenges and future directions.
Findings
Performance metrics tested on Intel Xeon Gold 5120
Identified initial performance failures and bottlenecks
Guidance on data structures and algorithm choices for OCaml implementations
Abstract
OCaml is an industrial-strength, multi-paradigm programming language, widely used in industry and academia. OCaml was developed for solving numerical and scientific problems involving large scale data-intensive operations and one such classic application set is Graph Algorithms, which are a core part of most analytics workloads. In this paper, we aim to implement the graph benchmarks along with the performance analysis. Graph500 is one such serious benchmark which aims at developing data intensive applications requiring extreme computational power. We try to implement Graph Construction, BFS, Shortest-Path problems using the desired specifications and rules posed by graph500. This paper aims at providing a clear direction of choices of several data structures used, algorithms developed and pose a reason behind every step of program. The first few sections of the paper discusses a formal…
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Taxonomy
TopicsGraph Theory and Algorithms · Software Testing and Debugging Techniques · Parallel Computing and Optimization Techniques
