JuliaGPU/CUDA.jl

Summing a vector is faster than summing a multidimensional array

Open

#2,764 opened on Apr 28, 2025

View on GitHub
 (1 comment) (0 reactions) (0 assignees)Julia (274 forks)batch import
cuda arraygood first issueperformance

Repository metrics

Stars
 (1,408 stars)
PR merge metrics
 (Avg merge 5d 5h) (16 merged PRs in 30d)

Description

I am not sure if this is an expected behavior, but it seems that sum(vec(A)) could be much faster than sum(A) when A is a multi-dimensional array. Please see https://discourse.julialang.org/t/summing-a-vector-is-faster-than-summing-a-multi-dimensional-array-of-the-same-length-using-cuda/116711 for an MWE. Although this post is from about a year ago, I can reproduce matching results with CUDA v5.7.3.

Contributor guide

Research direction
Compare the implementations of sum for vectors and multidimensional arrays in CUDA.jl to identify performance bottlenecks.
Tech stack
None
Domain
performance
Issue type
Performance
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
Half day
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Fresh
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Mostly clear
Prerequisites
JuliaCUDA
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
30