cccl
oneMKL
cccl | oneMKL | |
---|---|---|
2 | 2 | |
815 | 570 | |
13.1% | 2.1% | |
9.8 | 8.5 | |
3 days ago | 5 days ago | |
C++ | C++ | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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.
cccl
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GDlog: A GPU-Accelerated Deductive Engine
https://github.com/topics/datalog?l=rust ... Cozo, Crepe
Crepe: https://github.com/ekzhang/crepe :
> Crepe is a library that allows you to write declarative logic programs in Rust, with a Datalog-like syntax. It provides a procedural macro that generates efficient, safe code and interoperates seamlessly with Rust programs.
Looks like there's not yet a Python grammar for the treeedb tree-sitter: https://github.com/langston-barrett/treeedb :
> Generate Soufflé Datalog types, relations, and facts that represent ASTs from a variety of programming languages.
Looks like roxi supports n3, which adds `=>` "implies" to the Turtle lightweight RDF representation: https://github.com/pbonte/roxi
FWIW rdflib/owl-rl: https://owl-rl.readthedocs.io/en/latest/owlrl.html :
> simple forward chaining rules are used to extend (recursively) the incoming graph with all triples that the rule sets permit (ie, the “deductive closure” of the graph is computed).
ForwardChainingStore and BackwardChainingStore implementations w/ rdflib in Python: https://github.com/RDFLib/FuXi/issues/15
Fast CUDA hashmaps
Gdlog is built on CuCollections.
GPU HashMap libs to benchmark: Warpcore, CuCollections,
https://github.com/NVIDIA/cuCollections
https://github.com/NVIDIA/cccl
https://github.com/sleeepyjack/warpcore
/? Rocm HashMap
DeMoriarty/DOKsparse:
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Hello World on the GPU (2019)
C++20 would be news to me. Do you have a reference? The closest I can find is https://github.com/NVIDIA/cccl which seems to be atomic and bits of algorithm. E.g. can you point to unordered_map that works on the target?
I think some pieces of libc++ work but don't know of any testing or documentation effort to track what parts, nor of any explicit handling in the source tree.
oneMKL
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Stable Diffusion on AMD RDNA™ 3 Architecture
I think there's already been work done to just use intel MKL on any device: https://github.com/oneapi-src/oneMKL
- Developing in heterogeneous environment with the best HPC libraries
What are some alternatives?
stdgpu - stdgpu: Efficient STL-like Data Structures on the GPU
oneDNN - oneAPI Deep Neural Network Library (oneDNN)
cuCollections
kokkos-kernels - Kokkos C++ Performance Portability Programming Ecosystem: Math Kernels - Provides BLAS, Sparse BLAS and Graph Kernels
DOKSparse - sparse DOK tensors on GPU, pytorch
peakperf - Achieve peak performance on x86 CPUs and NVIDIA GPUs
Taskflow - A General-purpose Parallel and Heterogeneous Task Programming System
nekRS - our next generation fast and scalable CFD code
OpenCL-Wrapper - OpenCL is the most powerful programming language ever created. Yet the OpenCL C++ bindings are cumbersome and the code overhead prevents many people from getting started. I created this lightweight OpenCL-Wrapper to greatly simplify OpenCL software development with C++ while keeping functionality and performance.
ArrayFire - ArrayFire: a general purpose GPU library.
gdlog
monolish - monolish: MONOlithic LInear equation Solvers for Highly-parallel architecture