NAnateb2022·Feb 3, 2026Submission
Wave: Python Domain-Specific Language for High Performance Machine Learning
1 points · Open discussioniree-org
wave
Python2026–2026
iree-org / wave
wave
Wave: Python Domain-Specific Language for High Performance Machine Learning
2Distinct people
2Mentions
0Explicit recommenders
64GitHub stars
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What it is
Wave: Python Domain-Specific Language for High Performance Machine Learning
GitHub
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This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.
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Mentions over time
HN mentions by hour2 dated mentions
Observed mentions: 2026-02-03 15:21:47 UTC to 2026-02-03 15:37:54 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC. One observed period does not establish a trend.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Feb 3, 15:00 | 2026-02-03 15:00:00 UTC | 2026-02-03 16:00:00 UTC | 2 | 1 | 1 |
What Hacker News says
2 sourcesCompany: AMD
Role: GPU Performance Software Development Engineer
Location: San Jose, CA (see posting for details)
We’re building Wave, a high-performance GPU programming language and compiler for machine learning workloads. Wave combines a Python-embedded DSL with an MLIR-based compiler stack to give engineers explicit control over GPU kernel performance.
We’re looking for a low-level GPU performance engineer to own end-to-end performance of Wave’s kernels.
You’ll work on
• Hand-tuned GPU kernels (GEMM, Attention, MoE, decoding)
• Instruction-level optimization: memory, registers, scheduling, wave/warp behavior
• HIP/CUDA, GPU intrinsics (MFMA/MMA), and inline assembly
• MLIR dialects, lowering pipelines, and performance-critical compiler passes
• Profiling via disassembly, counters, rocprof/Nsight
Wave codebase: https://github.com/iree-