fastmachinelearning/hls4ml
Machine learning on FPGAs using HLS
Star History
Momentum
+54
STARS · LAST 30 DAYS
2
PER DAY
#246
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +14 | +54 | +180 |
| Per day | 2 | 2 | 2 |
| Forks gained | +3 | +12 | +30 |
hls4ml gained 54 stars in the last 30 days, about 2 a day, and now has 2.2K. It is about 9 years old and has averaged roughly 241 stars a year. It ranks #246 among Python repositories and #1,796 across all languages on GitHubRepo.
Trending Record
6
DAYS ON TRENDING
#434
BEST RANK
Sep 23, 2026
FIRST APPEARANCE
Active
STATUS TODAY
hls4ml has maintained a continuous presence across global trending indexes, peaking at #434. Below is the 30-day activity profile:
💡 Overview
hls4ml is an open-source project written in Python: Machine learning on FPGAs using HLS.
Engineered for speed, consistency, and developer ease, it solves common hurdles in fpga, hls, intel-hls. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install hls4ml⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
hls4ml coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Production System Integration
Embed hls4ml into Python backend services to handle core application logic.
CI/CD Automated Pipelines
Run automated validation, builds, and integration suites during deployments.
Developer Tooling & Workflows
Accelerate developer onboarding with pre-configured project utilities.
Open Source Extension
Fork and customize internal modules under the repository's open Apache-2.0 license.
🚀 Getting Started
Install hls4ml using your package manager: `pip install hls4ml`
Initialize your project workspace or configuration file for hls4ml.
Import hls4ml into your codebase or invoke it directly from your terminal.
Execute your test suite or run `hls4ml --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
fastmachinelearning/hls4ml is currently ranked #1,796 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
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|---|---|---|---|---|
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| #1,796 | fastmachinelearning/hls4ml This Project | Python | ★ 2.2K | |
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Frequently Asked Questions
What does hls4ml do? +
Machine learning on FPGAs using HLS
What language is hls4ml written in? +
The primary language is Python. Topics include: fpga, hls, intel-hls, keras, machine-learning.
Is hls4ml actively maintained? +
Yes, the last recorded push was on Sep 27, 2026 with 210 open issues being tracked.
How many stars does hls4ml have? +
hls4ml has 2,166 stars and 605 forks on GitHub.
How does hls4ml rank among GitHub repositories? +
With 2,166 stars, fastmachinelearning/hls4ml is ranked #1,796 globally across all repositories tracked on GitHubRepo and #246 among Python projects.
What license is hls4ml distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
