google / minimalloc
A lightweight memory allocator for hardware-accelerated machine learning
Why this job: matched by what the repo talks about: memory, learn, lightweight, machine
What it does
A key insight motivating our methodology is the discovery of a specific category of solutions -- which we call *canonical solutions* -- that correspond to the members of an algebraic lattice:
Get started
$ ./build/minimalloc --capacity=12 --input=benchmarks/examples/input.12.csv --output=output.12.csv - Maintenance
- Inactive
- Last commit 7 months ago
- Stars
- 196
- On GitHub
- Licence
- Apache-2.0
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.1.0
- Released 3 years ago
- Built with
- C++
- 58% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 50% closed
- 3 still open
- Pull requests
- 8 merged
- 1 waiting
- Releases
- 1
- 0 in the last year
More: languages, topics and project record
Languages
- C++ 58%
- Python 40%
- Jupyter Notebook 1%
- CMake 1%
Topics
- asplos
- asplos23
- combinatorial-optimization
- compiler
- hardware-acceleration
- machine-learning
- memory-allocation
- rectangle-packing
- static-analysis
Project record
- JobAgent memory
- StatusListed
- Commits128
- Forks18
- Watching5
- Stars in 28 days+2
- CreatedNov 23, 2022
- First seen by usNov 7, 2026
- CheckedNov 8, 2026