DR_EVT: HPC Job Scheduler Simulator

Documentation Status License

Discrete Event-Driven Simulator for High-Performance Computing Job Schedulers

DR_EVT simulates HPC job scheduling policies with EASY and CONSERVATIVE backfilling implementations. Uniquely supports online simulation via gRPC, enabling coordinated multi-cluster simulations in a distributed fashion and digital-twin scheduler interacting in real-time.

Scheduler behavior is verified against a from-scratch Python reference implementation (consistency check between implementations, not independently derived ground truth).

Development

Documentation

Getting Started

Start here if you’re new to DR_EVT:

User Guide

Complete guide for running simulations:

Algorithm and Testing

APIs

  • Streaming API - Online/incremental simulation API

  • Python API - Python bindings reference

  • gRPC Client/Server - Network-exposed streaming API, including the MPI-based multi-client/multi-server test harness

Development

For contributors and maintainers:

Project Status

Version: 1.0

Scheduling Policies:

  • Backfill: EASY and CONSERVATIVE (fully implemented)

  • Priority: FCFS, an alternative FCFS implementation (for testing), FCFS with conservative/no backfilling support, SJF, LJF

APIs:

  • Streaming API: Online/incremental simulation, including genuinely new jobs (append_job()/append_jobs()) not just ones already in a preloaded trace

  • gRPC Service: Network-exposed streaming API for multi-cluster coordination

  • Python Bindings: Batch mode and the core streaming/monitoring API; some Sim_Params fields and Simulation methods (including append_job()/append_jobs()) aren’t bound yet - see Python API

Test Suite: 150+ tests across comprehensive/unit/feature/append-job/progressive-loading/config/gRPC/scale/replay categories (see Testing Guide for the current breakdown and how to run them).

About

DR_EVT simulates discrete event-driven HPC job scheduling with:

  • EASY and CONSERVATIVE backfilling implementations, verified against an independent Python reference implementation (consistency check, not mathematical ground truth - see Testing Guide)

  • gRPC-based online simulation service enabling coordinated multi-cluster simulations in a distributed fashion and digital-twin scheduler interacting in real-time

  • Replay and simulation modes for both offline analysis and online operation

  • Streaming API for incremental job submission and online scheduling decisions

  • Real HPC trace support (Lassen format) plus simpler CSV format

  • Comprehensive test suite covering correctness, differential comparisons, and large-scale scenarios

Developed at Lawrence Livermore National Laboratory.