In person Rust June 2025 at AWS in Tel Aviv
2025.06.08 In person Rust June 2025 at AWS in Tel Aviv
In between the full-length presentations we'll have a few spots for lightning talks.
The event is hosted by Amazon / AWS.
Pizza and beer are sponsored by Eureka Labs.
Presentations
Power up NodeJS with Rust (Hebrew)
How rust can help to improve performance inside NodeJS/TS ecosystem.
- Presentation of napi-rs.
- Use case.
- Integration of rust inside a NestJS project.
- Benchmark and performance comparison.
Speakers
From TensorFlow to PyTorch with some help from Rust (Hebrew)
When moving a machine learning project from TensorFlow to PyTorch, we wanted to keep using our existing training data files that were in the TFRecord format. Unfortunately, there was no good method of reading this format from PyTorch without adding TensorFlow as a dependency, and even that caused performance problems.
To address this, I wrote rustfrecord, a Python package written in Rust with the help of PyO3, and published to PyPI using Maturin.
In the talk I'll discuss the problem, the solution, and what can be learned from this for other projects.
Speakers
To copy to Meetup
Title: In person Rust June 2025 at AWS in Tel Aviv
Date: 2025.06.08
Start: 18:00
In between the full-length presentations we'll have a few spots for lightning talks.
The event is hosted by Amazon / AWS.
Pizza and beer are sponsored by Eureka Labs.
* Power up NodeJS with Rust by Ariel Boukris
Language: (Hebrew)
Length: 40 min
How rust can help to improve performance inside NodeJS/TS ecosystem.
- Presentation of napi-rs.
- Use case.
- Integration of rust inside a NestJS project.
- Benchmark and performance comparison.
* From TensorFlow to PyTorch with some help from Rust by Gavrie Philipson
Language: (Hebrew)
Length: 40 min
When moving a machine learning project from TensorFlow to PyTorch, we wanted to keep using our existing training data files that were in the TFRecord format. Unfortunately, there was no good method of reading this format from PyTorch without adding TensorFlow as a dependency, and even that caused performance problems.
To address this, I wrote rustfrecord, a Python package written in Rust with the help of PyO3, and published to PyPI using Maturin.
In the talk I'll discuss the problem, the solution, and what can be learned from this for other projects.