| Commit message (Collapse) | Author | Age | Files | Lines |
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- Multi-thread GEMM utilizes existing RS thread pool on top of
Eigen.
- Large matrix-matrix multiplication is decomposed into multiple
tiled matrix-matrix multiplications. Each thread iterates on
the unfinished works.
- The tiling applies to ONLY ONE dimension of each input matrix,
and whether to tile X or Y depends on the transpose of the matrix.
- The performance increase is proportional to the number of
available CPU cores, for sufficiently large matrices.
Test: CTS test (rsblas) pass on Angler, Fugu and new devices.
Performance test with RsBlasBenchmark and RsNeuralNet demo
on Anger, Ryu, Seed, Shamu, Volantis, Fugu and new devices,
showing roughly 70%(Volantix 2 core) ~ 400+%(Angler 8 core) perf gain.
Change-Id: If96f4119fd34d5d9d98a2542801495e7ffe577ae
(cherry picked from commit 41ab8faaf0d90238d42d8e2bbb7177467c10b4f6)
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Change-Id: I26fcaebcca828388ef6fe53c6e9e4db8e60dd4d9
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Change-Id: Id084ac7b53ea0b3c61311b4f4c78312f397b7c5f
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non-optimal path for armv7 without NEON.
- gemmlowp will handle the optimal path for x86, NEON and aarch64
Change-Id: I67ce4c1e5b3195017a3d46895a8ce096682bc172
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and dlsym.
Change-Id: I3ade3ad2802f3b8e5fc5661319b98a6212e6d8a2
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gemmlowp.
Change-Id: I5bcfd0fa988d8075e70272f277d7d7fab93d5fea
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bug: 22184114
Change-Id: I6ec212f8d5feb46fc9d0f97862b206978af1675b
(cherry picked from commit 22cb808b0dfc9bd514d2e19b302a97f8455b5731)
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Bug: 20306487
Change-Id: Ic83cb04cac153a7556f5d516e8f5ec88b5527b6f
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bug: 21028875
Change-Id: Ia2d85a265f6e4a2617373f99b5c7bdc3810a7f24
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Change-Id: If91cbf969c75e01afc6d93b204bc8167180c9ef9
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Change-Id: Ia948afa2bc4af22f99323618738d5eb7d415ca97
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Change-Id: If4b1267dfd42d6dd65bedf20c0b674479eefab35
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Change-Id: I9b920900b4cb8b27e2ab27386d05f4175142d6b2
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Change-Id: I8e776b2ffdbac09a73924035eee2eca0a12facb3
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