Ikra: a Ruby dialect for GPGPU
GPGPU is attractive for its cost-performance, yet not easy to write programs. We propose a programming language implementation Ikra that generates GPGPU programs from Ruby programs. It allows the programmers to develop GPGPU code, including the kernel parts, in Ruby.
Source code
https://prg-titech.github.io/ikra-ruby/
Related Projects
The spin-off projects cover language implementations other than Ruby, and formal verification.
- DynaSOAr: Efficient Parallel Object Allocator for GPGPU
- Proof of Soundness of Concurrent Separation Logic for GPGPU in Coq
- Sanajeh: a Python DSL for GPGPU
News
- Keynote Talk on High-Level Programming Abstractions for GPGPU at CTHPC2022
- Seiichi Tejima Doctoral Dissertation Award, Matthias Springer, 2021, Memory-Efficient Object-Oriented Programming on GPUs
- Springer received Seiichi Tejima Doctoral Dissertation Award
- Masuhara’s Keynote Talk on Object Support for GPGPU at APLAS’20
- Paper on Dynamic Mem. Allocation on GPUs at ECOOP 2019
- Doctoral thesis defense by Matthias Springer
- Paper & Poster Presentation at ISMM 2019
- Springer won the First Place at the ACM Student Research Competition at SPLASH 2018
- Paper at ARRAY 2018
- Paper/Poster at WPMVP 2018 and CGO 2018 SRC
- Paper Presentation at ARRAY 2017
- Poster Presentations at PPL 2017
- Paper Presentation at ARRAY 2016
- Paper/Poster Presentations at PPL 2016
- Asakura presented master’s thesis, and Okugawa, Taya, and Watanabe presented bachelor’s thesis
- Poster presentation on Ikra at ISP2S2
- Nishiguchi, Murakami and Shao presented Master’s Theses
Older source code
- version 0.2 (ahead-of-time compiler)
- version 0.3 @ RubyGems