CUDA Graph Compute Function Refactor (precursor for performance improvements) #11042
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FYI: setting Status to Draft whilst I investigate the failed tests. |
I think you just need to make the functions |
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…meters) to separate function for improved readability.
…aluation and capture to its own function.
…on for improved readability.
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Ok, third time's a charm. My first try lacked the I strongly suggest to review commit by commit. Its easier to see there that not much has happened. |
slaren
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Jan 10, 2025
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I implemented your requested changes. The single test failure looks like a CI / runner issue. |
slaren
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Jan 13, 2025
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…e improvements) (ggml-org#11042) * Refactor: Moves cuda graph executable update step to separate function. * Refactor: Moves cuda graph update check to separate function. * Refactor: Moves cuda graph maintenance (update or adjusting copy parameters) to separate function for improved readability. * Fix: Adds missing reference to maintain_cuda_graph() definition. * Refactor: Improves structure and abstractions by moving CUDA graph evaluation and capture to its own function. * Refactor: Moves node graph checks and copy ops into individual function for improved readability. * Refactor: Removes code permanently excluded from compilation to increase readability. * Style: Adds missing newline * Style: Consolidates several neighboring '#ifdef USE_CUDA_GRAPH' into a single one * Refactor: Makes 'cuda_graph_update_required' a local variable * remove double lines between functions --------- Co-authored-by: slaren <[email protected]>
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…e improvements) (ggml-org#11042) * Refactor: Moves cuda graph executable update step to separate function. * Refactor: Moves cuda graph update check to separate function. * Refactor: Moves cuda graph maintenance (update or adjusting copy parameters) to separate function for improved readability. * Fix: Adds missing reference to maintain_cuda_graph() definition. * Refactor: Improves structure and abstractions by moving CUDA graph evaluation and capture to its own function. * Refactor: Moves node graph checks and copy ops into individual function for improved readability. * Refactor: Removes code permanently excluded from compilation to increase readability. * Style: Adds missing newline * Style: Consolidates several neighboring '#ifdef USE_CUDA_GRAPH' into a single one * Refactor: Makes 'cuda_graph_update_required' a local variable * remove double lines between functions --------- Co-authored-by: slaren <[email protected]>
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…e improvements) (ggml-org#11042) * Refactor: Moves cuda graph executable update step to separate function. * Refactor: Moves cuda graph update check to separate function. * Refactor: Moves cuda graph maintenance (update or adjusting copy parameters) to separate function for improved readability. * Fix: Adds missing reference to maintain_cuda_graph() definition. * Refactor: Improves structure and abstractions by moving CUDA graph evaluation and capture to its own function. * Refactor: Moves node graph checks and copy ops into individual function for improved readability. * Refactor: Removes code permanently excluded from compilation to increase readability. * Style: Adds missing newline * Style: Consolidates several neighboring '#ifdef USE_CUDA_GRAPH' into a single one * Refactor: Makes 'cuda_graph_update_required' a local variable * remove double lines between functions --------- Co-authored-by: slaren <[email protected]>
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Hi All,
I am working on improving llama.cpp's CUDA graph performance on behalf of NVIDIA.
In preliminary testing, we are seeing up to 3% of performance gain by overlapping CPU and GPU work, and by improving CPU -> GPU copy scheduling on a high end system. The changes are likely to be even more impactful on less capable hardware.
To pave the way for these changes (and to provide readable diffs), I first isolated the cosmetic changes in this PR.
This PR does not contain any changes in the logic. It merely slims down the
ggml_backend_cuda_graph_compute()by moving certain loops and other subtasks of the original function into 5 new functions.These changes considerably improve the readability and future maintainability of this part of the CUDA backend.
Should I add prefixes to the new function names, and if so, what do you suggest?
@agray3 @mtavenrath