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>
76 lines
2.7 KiB
C++
76 lines
2.7 KiB
C++
// Step 1978: CUDALibraryProfile
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//
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// t1: buildLedger has cublas at 0.99 for compute.matrix
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// t2: cufft/compute.fft = 0.99
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// t3: thrust/compute.parallel = 0.97
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// t4: cudnn/compute.ml.inference = 0.99
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// t5: cublas/compute.statistics is not applicable (score 0 / notApplicable)
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#include "CUDALibraryProfile.h"
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#include <iostream>
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namespace ws = whetstone;
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static int p = 0, f = 0;
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#define T(n) { std::cout << " " << #n << "... "; }
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#define P() { std::cout << "PASS\n"; ++p; }
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#define F(m) { std::cout << "FAIL: " << m << "\n"; ++f; }
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#define C(c, m) if (!(c)) { F(m); return; }
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void t1() {
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T(cublas_compute_matrix_0_99);
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auto ledger = ws::CUDALibraryProfile::buildLedger();
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C(ledger.score("cublas", "compute.matrix") == 0.99f, "cublas/compute.matrix = 0.99");
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auto rec = ledger.get("cublas", "compute.matrix");
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C(rec.has_value(), "record present");
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C(!rec->preferredAPIs.empty(), "preferredAPIs non-empty");
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bool hasSgemm = false;
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for (const auto& api : rec->preferredAPIs)
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if (api.find("cublasSgemm") != std::string::npos) hasSgemm = true;
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C(hasSgemm, "cublasSgemm in preferredAPIs");
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P();
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}
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void t2() {
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T(cufft_compute_fft_0_99);
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auto ledger = ws::CUDALibraryProfile::buildLedger();
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C(ledger.score("cufft", "compute.fft") == 0.99f, "cufft/compute.fft = 0.99");
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auto rec = ledger.get("cufft", "compute.fft");
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C(rec.has_value(), "cufft record present");
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C(!rec->preferredAPIs.empty(), "cufft preferredAPIs non-empty");
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P();
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}
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void t3() {
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T(thrust_compute_parallel_0_97);
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auto ledger = ws::CUDALibraryProfile::buildLedger();
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C(ledger.score("thrust", "compute.parallel") == 0.97f, "thrust/compute.parallel = 0.97");
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C(ledger.score("thrust", "compute.sort") == 0.97f, "thrust/compute.sort = 0.97");
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P();
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}
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void t4() {
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T(cudnn_ml_inference_0_99);
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auto ledger = ws::CUDALibraryProfile::buildLedger();
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C(ledger.score("cudnn", "compute.ml.inference") == 0.99f, "cudnn/ml.inference = 0.99");
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C(ledger.score("cudnn", "compute.ml.training") == 0.97f, "cudnn/ml.training = 0.97");
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P();
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}
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void t5() {
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T(cublas_statistics_not_applicable);
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auto ledger = ws::CUDALibraryProfile::buildLedger();
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// cublas/compute.statistics has notApplicable=true, score=0
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C(ledger.score("cublas", "compute.statistics") == 0.0f, "cublas/compute.statistics = 0");
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auto rec = ledger.get("cublas", "compute.statistics");
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C(rec.has_value(), "record exists");
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C(rec->notApplicable, "notApplicable = true");
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P();
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}
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int main() {
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std::cout << "Step 1978: CUDALibraryProfile\n";
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t1(); t2(); t3(); t4(); t5();
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std::cout << "\n" << p << "/" << (p + f) << " passed\n";
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return f > 0 ? 1 : 0;
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}
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