# stotko/stdgpu

stdgpu: Efficient STL-like Data Structures on the GPU

Repository: https://github.com/stotko/stdgpu
Canonical: https://ross.abutalabs.com/products/stdgpu
Homepage: https://stotko.github.io/stdgpu/
Language: C++
License: Apache-2.0
License Family: permissive
Topics: gpu, gpu-computing, gpu-acceleration, gpgpu, data-structures, stl, stl-like, stl-containers, cpp, cpp17, cpp20, modern-cpp, cuda, openmp, rocm, hip
Last push: 2026-07-08T18:31:43+00:00

## Health v2 (maintenance only)
Score: 64/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 91, release rhythm 8, longevity 100
- inputs: {"age_days": 2574, "days_push": 56, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1270, forks 102 (observed 2026-08-28T04:04:11.904151+00:00)

## What it is
stdgpu is a lightweight C++17 library providing STL-like generic data structures (vector, unordered_map, unordered_set, deque, queue, stack, bitset, atomics) for GPU computing. It supports CUDA, OpenMP, and experimental HIP backends and interoperates with thrust.

## Use cases
- use hash maps and sets on the GPU in CUDA kernels
- STL-like containers for GPU programming in C++
- manage dynamic data structures on GPU memory
- write portable GPU code across CUDA, HIP, and OpenMP
- concurrent insertion into GPU unordered_map from parallel kernels
- replace thrust with richer container support for GPU algorithms

## When to choose
- you need associative or dynamic containers (maps, sets, deques) on the GPU rather than just contiguous arrays
- you want STL-familiar APIs and backend-agnostic code across CUDA/HIP/OpenMP
- you already use thrust and need data management beyond contiguous storage

## When to avoid
- you only need simple contiguous arrays and GPU algorithms - thrust or ArrayFire may suffice
- you need a full GPU algorithm/BLAS ecosystem rather than a container library
- you require production HIP support - that backend is still experimental

## Facets
- artifact type: library
- maturity: active
- function: gpu-computing, concurrency, developer-tools
- domain: gpu-computing, developer-tools
- platform: cpp, windows
- tags: stl-containers, gpgpu, hip, openmp, data-structures, cpp17, cpp20, algorithms, gpu, cuda, linux, macos

## Member repositories
- stotko/stdgpu (main) score 64

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:11.904151+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T05:03:28.232606+00:00, confidence not recorded.
  - readme: https://github.com/stotko/stdgpu (fetched 2026-08-28T04:04:11.904151+00:00, sha 0ae5ee7b1189)
  - homepage: https://stotko.github.io/stdgpu/ (fetched 2026-08-29T12:14:54.278637+00:00, sha c074bab12c35)
- Data as of 2026-08-30T08:39:29.467469+00:00.