# ispc/ispc

Intel® Implicit SPMD Program Compiler

Repository: https://github.com/ispc/ispc
Canonical: https://ross.abutalabs.com/products/ispc
Language: C++
License: BSD-3-Clause
License Family: permissive
Topics: ispc, programming-language, compiler, intel, simd, spmd
Last push: 2026-07-22T22:26:23+00:00

## Health v2 (maintenance only)
Score: 89/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 93, release rhythm 78, longevity 100
- inputs: {"age_days": 5552, "days_push": 42, "days_rel": 69, "gap_med": 40.0, "n_releases_24m": 13}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2945, forks 351 (observed 2026-08-28T04:07:31.133993+00:00)

## What it is
Intel ISPC is a compiler for a C-based SPMD (single program, multiple data) language that targets SIMD vector units on CPUs and GPUs. It lets programmers write serial-looking code that compiles to wide-vector instructions, delivering significant speedups without hand-written intrinsics.

## Use cases
- compile C-like SPMD code to SIMD instructions
- speed up numeric kernels on AVX/SSE vector units
- write high-performance code without intrinsics
- parallelize computation across cores and vector lanes
- target GPUs with a C-based language

## When to choose
- you need SIMD performance but want to avoid assembly or intrinsics
- your workload is data-parallel and benefits from vectorization
- you want portable high-performance kernels across CPU architectures

## When to avoid
- your code is inherently serial or branch-heavy
- you need a general-purpose language rather than a performance kernel compiler
- your target hardware lacks SIMD vector units

## Facets
- artifact type: cli-tool
- maturity: stable
- function: compiler, programming-language, gpu-computing
- domain: compilers, programming-languages, performance
- platform: windows, cpp
- tags: simd, spmd, ispc, vectorization, high-performance-computing, compiler, linux, macos

## Member repositories
- ispc/ispc (main) score 89

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:31.133993+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 2026-08-30T08:31:35.171039+00:00, confidence not recorded.
  - readme: https://github.com/ispc/ispc (fetched 2026-08-28T04:07:31.133993+00:00, sha 83e5d4d64b08)
- Data as of 2026-08-30T08:39:29.467469+00:00.