Individual skill

nvshmem-enable-tma

Prepare or review NVSHMEM CUDA kernels for TMA SMEM registration and direct-SMEM transfers. Do not use for unrelated CUDA tuning.

skills/nvshmem-enable-tma/SKILL.md

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Repository stars (not skill ratings): 3,931
Repository last updated: Nov 11, 2026
License: Apache-2.0

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nvshmem Declared skill tag
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BENCHMARK.mddoc · 7,671 bytes
SKILL.mdcore · 9,242 bytes
SKILL.mdcore · 9,242 bytes
SKILL.mdcore · 9,242 bytes
SKILL.mdcore · 9,242 bytes
SKILL.mdcore · 9,242 bytes
SKILL.mdcore · 9,242 bytes
evals/evals.jsonasset · 6,179 bytes
evals/files/cuda-transpose.cuasset · 628 bytes
evals/files/direct-smem-put.cuasset · 908 bytes
evals/files/gmem-staging.cuasset · 872 bytes
evals/files/multi-node-put.cuasset · 527 bytes
references/direct-smem-put.mddoc · 2,009 bytes
references/gmem-staging.mddoc · 1,256 bytes
references/registration-and-launch.mddoc · 6,886 bytes
references/validation-and-troubleshooting.mddoc · 2,543 bytes
skill-card.mddoc · 4,306 bytes
skill.oms.sigasset · 6,553 bytes

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# Enable TMA in NVSHMEM Applications

## Purpose

Prepare an application for NVSHMEM's TMA-backed device-side transfers without changing its put/get APIs or unrelated kernels. Assess the target, choose the correct shared-memory path, make the smallest safe change, and explain launch-time requirements.

## Prerequisites

- Require readable CUDA/C++ source for a patch or code review. A static assessment needs no GPU, installed NVSHMEM runtime, or cluster access.
- Require an NVSHMEM 3.7.0-or-newer development environment and CUDA toolchain only when compiling.
- Require SM90-or-newer GPUs and peer GPU load/store reachability such as NVLink only when validating TMA execution or performance.
- CFT requires TMA.

## Reference Routing