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