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# Introduction
CUTLASS is a collection of templated CUDA C++ abstractions for implementing
CUTLASS is a collection of CUDA C++ template abstractions for implementing
high-performance matrix-multiplication (GEMM) at all levels and scales within CUDA.
It incorporates the same stragies for data movemement and hierarchical decomposition
It incorporates the same strategies for data movement and hierarchical decomposition
that are used to implement cuBLAS. CUTLASS decomposes these “moving parts” into
reusabe, modular software components abstracted by C++ template classes. These
thread-wide, warp-wide, block-wide, and device-wide abstractions can be specialized
by custom tiling sizes, data types, and other algorithmic policy. This flexibility
allows them to be used as building blocks within custom kernels and applications.
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.
To support a wide variety of applications, CUTLASS provides extensive support for
mixed-precision computations, providing specialized data-movement and