perf: reduce redundant CUDA initialization and synchronization - #190
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chen2021673 wants to merge 1 commit into
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perf: reduce redundant CUDA initialization and synchronization#190chen2021673 wants to merge 1 commit into
chen2021673 wants to merge 1 commit into
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Chamberlain0w0
approved these changes
Jul 31, 2026
kilinchange
requested changes
Jul 31, 2026
| class AutogradLinearForwardTest : public infini_train::test::InfiniTrainTest {}; | ||
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| namespace { | ||
| std::shared_ptr<Tensor> CopyToCPU(const std::shared_ptr<Tensor> &tensor) { |
Collaborator
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直接在调用处用 Tensor->to(device) 函数就行吧，不需要额外封装工具函数，其他测试文件同理，
| class AutogradNormalizationBackwardTest : public infini_train::test::InfiniTrainTest {}; | ||
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| namespace { | ||
| void ExpectValues(const std::shared_ptr<Tensor> &tensor, float expected) { |
Collaborator
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其他测试函数似乎都用到了类似的对比逻辑，建议封装成 tests 里的统一工具函数供所有测例使用。
| class AutogradReductionBackwardTest : public infini_train::test::InfiniTrainTest {}; | ||
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| void ExpectValues(const std::shared_ptr<Tensor> &tensor, const std::vector<float> &expected) { |
Collaborator
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同上，其他测试文件里直接写在测例里的精度对比逻辑，也都改成调用统一的精度对比工具函数吧。
Collaborator
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麻烦在所有涉及 loss 统计位置调整的地方补充注释，说明将 loss 拷贝到 CPU 并读取标量放在 backward 之后，是为了避免在反向开始前触发 D2H 同步、阻塞反向任务提交，从而让反向 kernel 尽早启动。
- defer loss host synchronization until after backward across training paths - skip zero fills when CUDA kernels or cuBLAS fully overwrite outputs - retain and document initialization required by partial-write paths - add CPU and CUDA numerical tests for affected operators
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