mpl
HPCInfo
mpl | HPCInfo | |
---|---|---|
7 | 1 | |
287 | 259 | |
15.0% | - | |
8.4 | 8.6 | |
about 2 months ago | 10 days ago | |
Standard ML | C | |
GNU General Public License v3.0 or later | MIT License |
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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
HPCInfo
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Open source arm64 fortran?
I wrote a script to make it easy for people to install and try new Flang: https://github.com/jeffhammond/HPCInfo/blob/master/buildscripts/llvm-git.sh
What are some alternatives?
cakeml - CakeML: A Verified Implementation of ML
h5cpp - C++17 templates between [stl::vector | armadillo | eigen3 | ublas | blitz++] and HDF5 datasets
LunarML - The Standard ML compiler that produces Lua/JavaScript
libgrape-lite - 🍇 A C++ library for parallel graph processing (GRAPE) 🍇
mlton - The MLton repository
mpl - A C++17 message passing library based on MPI
1ml - 1ML prototype interpreter
parallel-kd-tree - Parallel k-d tree with C++17, MPI and OpenMP
ppci - A compiler for ARM, X86, MSP430, xtensa and more implemented in pure Python
arbor - The Arbor multi-compartment neural network simulation library.
install-mlkit - Action for installing MLKit
RaftLib - The RaftLib C++ library, streaming/dataflow concurrency via C++ iostream-like operators