HIP Threads: GPU power for teams without GPU experts
Source: AMD Developer Blog
If your CPU hotspots are hitting performance limits while your GPU sits idle, you can address both without needing GPU experts.
Your profiler shows the CPU hotspots clearly. GPUs could help, but many teams lack the specialized knowledge to tap into them.
Introducing HIP Threads: GPU acceleration minus the complexity
HIP Threads is a C++ concurrency library that lets you use AMD GPUs with the same mental model you already use for CPU multithreading—no kernel rewrites, no unfamiliar programming models. Just your trusted C++ patterns running on GPUs.
That’s it. Your code now runs on AMD GPUs.
Real results from real teams
| Application | Performance Gain | Time to Implement |
|---|---|---|
| SAXPY Operations | 6.4× faster1 | Days, not months |
| Ray Tracing | 2.9× faster2 | Days, not months |
| Sparse Matrix Multiply | 3.6× faster3 | Days, not months |
See claims RPS‑167, RPS‑168, and RPS‑169 in footnotes.
Who is HIP Threads for?
- C++ teams with CPU bottlenecks that see clear hotspots in their profiler.
- Developers without GPU expertise who can’t justify learning CUDA/AMD ROCm™.
- Tool vendors and platform teams who want simple GPU integration for their users.
Why some teams don’t use GPUs (and how we fix it)
Traditional GPU programming
- Learn new programming models (grids, blocks, warps).
- Rewrite working code into kernels.
- Justify months of refactoring to management.
- Hire GPU specialists or train the team for long‑term support.
With HIP Threads
- Use your existing C++ threading knowledge.
- Fits easily into your development environment.
- Port hotspots incrementally.
- See results in days, not months.
How it works
HIP Threads maps familiar C++ threading patterns to efficient GPU execution. It acts as a translator that speaks both the C++ developer and GPU hardware fluently, requiring no magic—just smart engineering that bridges the gap between CPU and GPU programming models.
Stop leaving performance on the table and start your GPU journey today
We’re actively working with developers, tool vendors, and platform teams who want GPU acceleration to be as approachable as CPU threading. Your GPUs are waiting, your hotspots are known—the only thing standing between you and significant performance gains is getting started. No GPU expertise required, no massive refactoring, just more performance.
Footnotes
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Testing by AMD (Feb 2026) on AMD Radeon™ AI PRO R9700 with ROCm 7.0.2 and AMDGPU driver 6.16.6, comparing HIP Threads on the GPU vs. standard threads on the CPU. System: AMD Ryzen™ 9 9900X, 64 GB DDR5‑4800, Ubuntu 24.04.2 LTS. RPS‑167. ↩
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Testing by AMD (Feb 2026) on the same hardware using the “Ray Tracing in One Weekend” rendering test. RPS‑168. ↩
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Testing by AMD (Feb 2026) on the same hardware using the Sparse Matrix Multiply (pwtk.mtx) test. RPS‑169. ↩