Leaderboard/DevOps/infra-skills
Last commit on July 10, 2026·Created on July 10, 2026

open-infra-skills/infra-skills

Performance profiling and workload optimization for AI training on Moore Threads MUSA GPUs
Combined rank
#486
across all skills
In DevOps
#10
category rank
Stars
140
+0.7% in last 7d
Forks
2
+100.0% in last 7d
Watchers
0
-100.0% in last 7d
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Description

This skill provides the technical framework for AI infrastructure and ML performance engineers to profile, benchmark, and debug training workloads on Moore Threads MUSA hardware. It focuses on increasing throughput while preserving numerical behavior during the transition from CUDA to MUSA.

Engineers can address distributed hangs, memory pressure, and kernel launch overhead using tools like the Moore Perf System and Moore Perf Compute. The guidance covers critical optimizations including FlashAttention, torch.compile, and FSDP2 to improve hardware utilization.

WHO IT'S FOR
AI infrastructure engineers
optimize AI training workloads on MUSA GPUs
ML performance engineers
migrate training performance from CUDA to MUSA
Distributed training specialists
debug distributed hangs and MCCL overhead
GPU kernel developers
analyze kernel launch and transfer overhead
30 Days of GitHub Stars
140 30d stars
Monthly change unavailable
Jul 7Jul 14Jul 21Jul 28Aug 5
Compatibility & Install
1 Skill · 1 Compatible agent · 3 categories · 1 install path
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Categories
DevOpsSoftware EngineeringDeveloper Tooling
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