From cd71b47e680a7fd5e402bb194aaa413ceb5c1dc6 Mon Sep 17 00:00:00 2001 From: "James D. Mitchell" Date: Mon, 20 Nov 2023 11:16:27 +0000 Subject: [PATCH] Optimize links in README + spelling --- .codespellrc | 2 +- README.md | 34 ++++++++++++++++++---------------- 2 files changed, 19 insertions(+), 17 deletions(-) diff --git a/.codespellrc b/.codespellrc index 4e78859a..9235a942 100644 --- a/.codespellrc +++ b/.codespellrc @@ -1,3 +1,3 @@ [codespell] -skip = ./third_party/simde,./.git,./benchmark/python,./experiments +skip = ./third_party/simde,./.git,./benchmark/python,./experiments,./gh-pages,./build ignore-words-list=shft diff --git a/README.md b/README.md index 0fabb0b5..a772e30c 100644 --- a/README.md +++ b/README.md @@ -2,18 +2,18 @@ High Performance Combinatorics in C++ using vector instructions v0.0.8 HPCombi is a C++17 header-only library using the SSE and AVX instruction sets, -and some equivalents, for very fast manipulation of combinatorial -objects such as transformations, permutations, and boolean matrices of small -size. The goal of this project is to implement various new algorithms and -benchmark them on various compiler and architectures. +and some equivalents, for very fast manipulation of combinatorial objects such +as transformations, permutations, and boolean matrices of small size. The goal +of this project is to implement various new algorithms and benchmark them on +various compiler and architectures. HPCombi was initially designed using the SSE and AVX instruction sets, and did not work on machines without these instructions (such as ARM). From v1.0.0 -HPCombi supports processors with other instruction sets also, via -[simd-everywhere](https://github.com/simd-everywhere/simde). It might be the -case that the greatest performance gains are achieved on processors supporting -the SSE and AVX instruction sets, but the HPCombi benchmarks indicate that -there are also still signficant gains on other processors too. +HPCombi supports processors with other instruction sets also, via [SIMD +Everywhere][]. It might be the case that the greatest performance gains are +achieved on processors supporting the SSE and AVX instruction sets, but the +HPCombi benchmarks indicate that there are also still significant gains on +other processors too. ## Authors @@ -29,10 +29,12 @@ there are also still signficant gains on other processors too. ## Thanks -- The development of HPCombi was partly funded by the - [OpenDreamKit](http://opendreamkit.org/) Horizon 2020 European Research - Infrastructure project (#676541), which the authors acknowledge with thanks. -- Thanks also to the - [simd-everywhere](https://github.com/simd-everywhere/simde) and - [catch2](https://github.com/catchorg/Catch2) authors and contributors for - their excellent libraries! +- The development of HPCombi was partly funded by the [OpenDreamKit][] Horizon + 2020 European Research Infrastructure project (#676541), which the authors + acknowledge with thanks. +- Thanks also to the [SIMD everywhere][] and [catch2][] authors and + contributors for their excellent libraries! + +[SIMD everywhere]: https://github.com/simd-everywhere/simde +[OpenDreamKit]: https://opendreamkit.org/ +[catch2]: https://github.com/catchorg/Catch2