Description
Saga – Scheduling Algorithms Gathered – is a Python toolkit/library for designing, comparing, and visualizing DAG-based computational workflow-scheduler performance on heterogeneous compute networks (also known as dispersed computing). It ships with a collection of scheduling algorithms, including classic heuristics (HEFT, CPOP), brute-force baselines, SMT-based optimizers, and more, all under one cohesive API.
The algorithms are all implemented in Python using a common interface. Scripts for validating and comparing the performance of the algorithms are also provided.
People
- Bhaskar Krishnamachari - University of Southern California - Professor
- Gabriel Twigg-Ho - Swinburne University, Australia - Undergraduate Student - Engineering
- Jared Coleman - Loyola Marymount University - Assistant Professor of Computer Science
- Jason Chamorro - Loyola Marymount University - Undergraduate Student - Computer Science
- Matias Martinez Gonzalez - Loyola Marymount University - Undergraduate Student - Information Systems and Business Analytics
- Nicholas Laus - Loyola Marymount University - Undergraduate Student - Computer Science
Publications
- Evaluating the Impact of Algorithmic Components on Task Graph Scheduling - JSSPP 2025 - The 28th Workshop on Job Scheduling Strategies for Parallel Processing - 06/03/2025
- PISA: An Adversarial Approach To Comparing Task Graph Scheduling Algorithms - To Appear at IPDPS 2025 - The 39th International Parallel and Distributed Processing Symposium - 06/03/2025
- Evaluating Scheduling Algorithms for Adaptive Orchestration in Federated Tactical Edge Cloud Environments - ICMCIS 2025 - The International Conference on Military Communication and Information Systems - 05/13/2025