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Article0 replies1,634 followingPosted 12 Jun 2026, 10:27 UTC78.7K views1,171 votes

Speed‑Up Large Matrix Multiplications in MATLAB with parfor

Learn how MATLAB’s Parallel Computing Toolbox can cut matrix‑multiplication time in half or more, the trade‑offs to watch for, and a step‑by‑step example you can run right now.

Community & Careers · Blog

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Tasadduq Burneyowner

Started12 Jun 2026, 10:27 UTC

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Community & Careers

Article0 replies3,692 followingPosted 09 Aug 2025, 05:28 UTC52.4K views3,447 votes

Optimizing MATLAB Parallel Loops with parfor: Design, Checks, and Pitfalls

When you have independent iterations, MATLAB’s parfor can give a near‑linear speedup. This guide covers the minimal design, trust boundaries, operational checks, failure modes, and when to switch to a full cluster.

Community & Careers · Guide

architecture

matlab parallel-computing

Community & Careers

Article0 replies836 followingPosted 10 Feb 2026, 20:28 UTC136.5K views3,205 votes

When ParallelMap Actually Speeds Up Your Wolfram Code

ParallelMap only speeds up Wolfram list processing when kernels are running, the list is large enough, and the function threads correctly. Here's how to diagnose and fix the common cases where it silently falls back to sequential execution.

Community & Careers · Blog

kernel-management wolfram-language parallel-computing

Community & Careers

Article0 replies1,396 followingPosted 26 Dec 2025, 06:18 UTC80.7K views1,584 votes

Optimizing OpenCL Memory: Choosing Between Global, Constant, and Local Storage

Learn how to choose between Global, Constant, and Local memory in OpenCL to eliminate memory latency bottlenecks and optimize kernel throughput using tiling and coalescing.

Community & Careers · Guide

gpu-optimization

opencl memory-management

Community & Careers

Article0 replies2,889 followingPosted 05 Sept 2025, 10:16 UTC61.7K views1,433 votes

Accelerating MATLAB Code with parfor: A Practical Task Guide

Learn how to replace a standard for-loop with parfor for parallel execution, verify worker usage, and troubleshoot common pitfalls. This guide walks you through prerequisites, step‑by‑step configuration, and recovery options.

Community & Careers · Guide

matlab parallel-computing loop-acceleration

Community & Careers

Article0 replies3,407 followingPosted 11 Nov 2025, 17:39 UTC56.1K views3,136 votes

Choosing Between @threads and pmap for Parallel Loops in Julia

Deciding between @threads and pmap in Julia depends on data volume and hardware. This guide compares shared-memory threading versus distributed processing for parallel loops.

Community & Careers · Guide

multithreading

julia distributed-computing

Community & Careers

Article0 replies2,303 followingPosted 31 Dec 2025, 17:44 UTC121.2K views3,736 votes

Accelerating MATLAB Computations: Choosing Between parfor and gpuArray

Deciding between parfor and gpuArray in MATLAB depends on your hardware and data size. This guide compares CPU multicore parallelism versus GPU SIMD acceleration for compute-intensive loops.

Community & Careers · Guide

gpu-acceleration

matlab parallel-computing

Community & Careers

Article0 replies3,621 followingPosted 02 May 2026, 12:45 UTC147.9K views903 votes

Speeding Up MATLAB Matrix Operations on a GPU with gpuArray

Move large MATLAB matrix and FFT workloads to a CUDA GPU with gpuArray: environment checks, transfer-overhead pitfalls, honest timing with wait(gpuDevice), and when the GPU is not worth it.

Community & Careers · Guide

gpuarray gpu-computing

matlab

Community & Careers

Article0 replies1,763 followingPosted 30 Nov 2025, 02:01 UTC106.3K views1,522 votes

Choosing Julia Parallelism: Shared‑Memory Threads vs Distributed Workers for Loop Workloads

When you need to speed up a loop‑heavy Julia program, decide between lightweight shared‑memory threading and heavyweight distributed workers. This guide compares the two, explains trade‑offs, and shows a concrete sum‑benchmark to help you pick the right model.

Community & Careers · Guide

multithreading

julia distributed-computing