mpl
mlkit
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| mpl | mlkit | |
|---|---|---|
| 7 | 2 | |
| 285 | 264 | |
| 16.8% | - | |
| 8.4 | 7.7 | |
| about 2 months ago | about 2 months ago | |
| Standard ML | Standard ML | |
| GNU General Public License v3.0 or later | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
mpl
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Garbage Collection for Systems Programmers
I'm one of the authors of this work -- I can explain a little.
"Provably efficient" means that the language provides worst-case performance guarantees.
For example in the "Automatic Parallelism Management" paper (https://dl.acm.org/doi/10.1145/3632880), we develop a compiler and run-time system that can execute extremely fine-grained parallel code without losing performance. (Concretely, imagine tiny tasks of around only 10-100 instructions each.)
The key idea is to make sure that any task which is *too tiny* is executed sequentially instead of in parallel. To make this happen, we use a scheduler that runs in the background during execution. It is the scheduler's job to decide on-the-fly which tasks should be sequentialized and which tasks should be "promoted" into actual threads that can run in parallel. Intuitively, each promotion incurs a cost, but also exposes parallelism.
In the paper, we present our scheduler and prove a worst-case performance bound. We specifically show that the total overhead of promotion will be at most a small constant factor (e.g., 1% overhead), and also that the theoretical amount of parallelism is unaffected, asymptotically.
All of this is implemented in MaPLe (https://github.com/mpllang/mpl) and you can go play with it now!
- MPL: Automatic Management of Parallelism
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Good languages for writing compilers in?
Maple is a fork of MLton: https://github.com/MPLLang/mpl
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Comparing Objective Caml and Standard ML
Some of us are still using SML for research and teaching, e.g. https://github.com/mpllang/mpl
- MaPLe Compiler for Parallel ML v0.3 Release Notes
- MPL-v0.3 Release Notes
mlkit
- [MLKit version 4.6.0](https://github.com/melsman/mlkit) is released
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Getting started with Standard ML
The developer mailing lists for Poly/ML and MLton are active and the maintainers are very friendly. The MLKit Github issues are active. Help needed for SML/NJ.
What are some alternatives?
cakeml - CakeML: A Verified Implementation of ML
smlpkg - Generic package manager for Standard ML libraries and programs
LunarML - The Standard ML compiler that produces Lua/JavaScript
HPCInfo - Information about many aspects of high-performance computing. Wiki content moved to ~/docs.
mlton - The MLton repository
sml-rmath - SML library for the Rmath library, with seven SML implementations/dialects
1ml - 1ML prototype interpreter
sml-bdb - Berkeley DB binding for Standard ML
ppci - A compiler for ARM, X86, MSP430, xtensa and more implemented in pure Python
sml-parseq - parallel sequences library in Standard ML