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Update README.md
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@@ -8,9 +8,9 @@ It incorporates the same strategies for data movement and hierarchical decomposi
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that are used to implement cuBLAS. CUTLASS decomposes these “moving parts” into
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reusable, modular software components abstracted by C++ template classes. These
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thread-wide, warp-wide, block-wide, and device-wide primitives can be specialized
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and tuned via custom tiling sizes, data types, and other algorithmic policy.
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The resulting flexibility simplifies their use as building blocks within custom
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kernels and applications.
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and tuned via custom tiling sizes, data types, and other algorithmic policy. The
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resulting flexibility simplifies their use as building blocks within custom kernels
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and applications.
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To support a wide variety of applications, CUTLASS provides extensive support for
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mixed-precision computations, providing specialized data-movement and
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