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Mpl Alternatives
Similar projects and alternatives to mpl
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TablaM
The practical relational programing language for data-oriented applications
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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Fable: F# |> BABEL
F# to JavaScript, TypeScript, Python, Rust and Dart Compiler
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AECforWebAssembly
A port of ArithmeticExpressionCompiler from x86 to WebAssembly, so that the programs written in the language can run in a browser. The compiler has been rewritten from JavaScript into C++.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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HPCInfo
Information about many aspects of high-performance computing. Wiki content moved to ~/docs.
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FunctionalPlus
Functional Programming Library for C++. Write concise and readable C++ code.
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completely-unscientific-benchmarks
Naive performance comparison of a few programming languages (JavaScript, Kotlin, Rust, Swift, Nim, Python, Go, Haskell, D, C++, Java, C#, Object Pascal, Ada, Lua, Ruby)
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better mpl alternative or higher similarity.
mpl reviews and mentions
Posts with mentions or reviews of mpl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-03-30.
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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
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A note from our sponsor - InfluxDB
www.influxdata.com | 18 Apr 2024
Stats
Basic mpl repo stats
7
284
8.4
about 1 month ago
MPLLang/mpl is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of mpl is Standard ML.
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
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