# GPU Kernels

This page is scoped conservatively: it covers what's confirmed about Tensormorph's compute-backend model, applied to kernel-level profiling. There is no local NVIDIA Nsight Compute reference in this workspace, and detailed kernel-metrics UI (a roofline chart, an occupancy calculator, and similar) is not a confirmed part of Tensormorph's design - treat any such feature as a plausible future direction, not documented fact.

Kernel-level profiling asks a narrower question than [runtime tracing](/docs/profiling/runtime-traces): not "what did this tensor's values look like," but "how efficiently did the compute that produced it actually run" - which specific kernel launch, on which backend, took how long.

## What's confirmed

Tensormorph's [GPU Backend Compatibility](/docs/reference/gpu-backend-compatibility) model already establishes the pieces a kernel-level view would build on: operations are placed across five backends (CPU, WebGPU, CUDA, ROCm, Metal) by capability and cost, and the **Compute panel** shows which backend actually served a given operation. A kernel-level profiling view, if you're looking for one, is the natural place to see *how well* that placement performed, not just which backend was chosen.

## Importing an external trace

Given the confirmed emphasis on interoperability elsewhere in Tensormorph (reading safetensors, ONNX, and Hub-hosted checkpoints without requiring a proprietary format first), the most likely path for deep kernel-level analysis is importing a trace already captured by a dedicated profiling tool for your target backend, rather than Tensormorph reimplementing a full kernel-level profiler for every backend it supports. Treat that as a reasonable expectation, not a documented feature.

## What to use instead, today

For CUDA workloads specifically, NVIDIA's own Nsight Compute (kernel-level) and Nsight Systems (timeline-level) tools remain the authoritative source for this kind of analysis until Tensormorph's own story here is finalized.

## Related resources

-   [GPU Backend Compatibility](/docs/reference/gpu-backend-compatibility) - the confirmed backend-placement model this page builds on.
-   [Runtime Traces](/docs/profiling/runtime-traces) - value-level (not kernel-level) runtime capture, which is confirmed and available today.
-   [Performance Baselines](/docs/profiling/performance-baselines) - comparing performance across two runs, independent of kernel-level detail.