Microbenchmarks | Micro benchmark comparison of Julia | Performance Testing library
kandi X-RAY | Microbenchmarks Summary
kandi X-RAY | Microbenchmarks Summary
This is a collection of micro-benchmarks used to compare Julia's performance against that of other languages. It was formerly part of the Julia source tree. The results of these benchmarks are used to generate the performance graph on the Julia homepage and the table on the benchmarks page.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of Microbenchmarks
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Community Discussions
Trending Discussions on Microbenchmarks
QUESTION
I'm working on an Rcpp sparse matrix class that uses both Rcpp::IntegerVector
(row/column pointers) and a templated std::vector
. The rationale is that overhead in deep-copying the integer pointer vectors (@i
, @p
) in extremely large sparse-matrices can be avoided by simply leaving them as pointers to R objects, and consistently, microbenchmarks show that this approach takes almost exactly half the time as conversion to Eigen::SparseMatrix
and arma::SpMat
while using less memory.
Bare-bones Rcpp sparse matrix class
...ANSWER
Answered 2021-Apr-14 at 14:38It's actually quite simple to create an Rcpp SparseMatrix class! I was overthinking it.
QUESTION
I'm using CUDA's WMMA API to multiply fragments on the GTX 1660 Ti. This GPU doesn't have Tensor Cores, but when I look at the SASS generated for my code I see HMMA.1688.F32 instructions, which are Tensor Core instructions! How can that happen?
Relevant information:
- NVIDIA confirming my card doesn't have Tensor Cores: https://www.nvidia.com/en-eu/geforce/10-series/ (Technology Features table comparing GTX 10, GTX 16 and RTX 20 Series).
- HMMA.1688.F32 instructions linked to Tensor Core units:
- https://developer.download.nvidia.com/video/gputechconf/gtc/2019/presentation/s9839-discovering-the-turing-t4-gpu-architecture-with-microbenchmarks.pdf
- https://ieeexplore.ieee.org/document/9139835 (account required to access, but more detailed)
ANSWER
Answered 2021-Mar-14 at 14:15For code binary compatibility, the "non-tensor-core" members of the Turing family have hardware in the SM that will process tensor core instructions, albeit at a relatively low throughput, compared to a tensor core unit.
QUESTION
I'm on the master
channel, and want to switch to the dev
. When I run
ANSWER
Answered 2020-Nov-17 at 03:30Run these commands:
QUESTION
I was wondering if there is a way to generate a fixed length random string in Clojure.
A quick search resulted in:
...ANSWER
Answered 2020-Sep-23 at 19:21Let me answer my own question:
QUESTION
My question is basically what the title says. Given some vector x
consisting of both TRUE
and FALSE
, keep only the first occurrence of TRUE
and set the rest to FALSE
.
A small example:
...ANSWER
Answered 2020-Apr-18 at 11:41This tweak of your vec_repl()
gives a small speedup for larger examples:
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