d7caaa8762
CUDALibraryProfile, CUDASymbolCatalog, ProjectStackDeclarator, ProofPipelineRunner, Sprint290IntegrationSummary. 25/25 tests passing. End-to-end proof: "GPU matrix multiply. JSON result serialization." -> cublas for compute.matrix, nlohmann_json for serialization.json. Phase 6: Library Dispatch COMPLETE (Sprints 286-290, steps 1958-1982). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
67 lines
2.9 KiB
C++
67 lines
2.9 KiB
C++
#pragma once
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// Step 1978: CUDALibraryProfile
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// Full CUDA capability ledger: cublas, cufft, thrust, cudnn.
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// Scores, preferredAPIs, and knownWeaknesses for each (library, domain) pair.
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#include "LibraryCapabilityLedger.h"
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namespace whetstone {
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class CUDALibraryProfile {
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public:
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static LibraryCapabilityLedger buildLedger() {
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LibraryCapabilityLedger ledger;
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// --- cublas ---
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ledger.set({"cublas", "compute.matrix", 0.99f,
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{"cublasSgemm()", "cublasDgemm()", "cublasSgemv()",
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"cublasCreate()", "cublasDestroy()"},
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{"requires-device-memory-management",
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"no-automatic-handle-lifecycle",
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"single-gpu-only-without-multi-gpu-wrappers"},
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false, "2026-03-02", "benchmark+api-analysis"});
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ledger.set({"cublas", "compute.statistics", 0.00f,
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{},
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{"not-applicable-for-statistics"},
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true, "2026-03-02", "api-analysis"});
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// --- cufft ---
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ledger.set({"cufft", "compute.fft", 0.99f,
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{"cufftPlan1d()", "cufftExecC2C()", "cufftDestroy()",
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"cufftPlanMany()"},
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{"requires-separate-cufft-handle-lifecycle",
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"complex-plan-setup-for-batched-transforms"},
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false, "2026-03-02", "benchmark"});
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// --- thrust ---
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ledger.set({"thrust", "compute.parallel", 0.97f,
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{"thrust::transform()", "thrust::reduce()", "thrust::copy()",
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"thrust::fill()", "thrust::for_each()"},
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{"host-device-copy-required-for-mixed-workloads"},
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false, "2026-03-02", "benchmark"});
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ledger.set({"thrust", "compute.sort", 0.97f,
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{"thrust::sort()", "thrust::stable_sort()",
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"thrust::sort_by_key()", "thrust::stable_sort_by_key()"},
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{"comparator-must-be-device-compatible"},
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false, "2026-03-02", "benchmark"});
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// --- cudnn ---
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ledger.set({"cudnn", "compute.ml.inference", 0.99f,
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{"cudnnConvolutionForward()", "cudnnActivationForward()",
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"cudnnPoolingForward()", "cudnnCreate()", "cudnnDestroy()"},
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{"workspace-memory-must-be-pre-allocated",
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"descriptor-setup-verbose"},
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false, "2026-03-02", "benchmark"});
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ledger.set({"cudnn", "compute.ml.training", 0.97f,
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{"cudnnConvolutionBackwardData()", "cudnnConvolutionBackwardFilter()",
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"cudnnActivationBackward()"},
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{"workspace-memory-must-be-pre-allocated",
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"gradient-accumulation-manual"},
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false, "2026-03-02", "benchmark"});
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return ledger;
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}
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};
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} // namespace whetstone
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