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When run against CuArray in CUDA.jl's test suite, two tests dominated GPU RSS without exercising anything the smaller sizes wouldn't: - linalg/kron: 32x64 * 128x16 produces a 4096x1024 result; halving each operand to 16x32 * 64x8 still covers all opa/opb transpose variants at ~16x less memory. - reductions/mapreducedim! large: the 5000x500 / 500x5000 / 1000000 sizes were picked to exceed the multi-element-reading threshold (~86k on typical GPUs). 1000x500 / 500x1000 / 500000 still clears that threshold on realistic devices. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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When run against CuArray in CUDA.jl's test suite, two tests dominated GPU RSS without exercising anything the smaller sizes wouldn't: