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CUTLASS 1.2

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![ALT](/media/images/gemm-hierarchy-with-epilogue-no-labels.png "Complete CUDA GEMM decomposition")
# CUTLASS 1.1
# CUTLASS 1.2
_CUTLASS 1.1.0 - September 2018_
_CUTLASS 1.2.0 - October 2018_
CUTLASS 1.1 is a collection of CUDA C++ template 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 strategies for hierarchical decomposition and data movement similar
to those used to implement cuBLAS. CUTLASS decomposes these "moving parts" into
@ -22,12 +22,19 @@ point (FP64) types. Furthermore, CUTLASS demonstrates CUDA's WMMA API for targe
the programmable, high-throughput _Tensor Cores_ provided by NVIDIA's Volta architecture
and beyond.
CUTLASS 1.1 is described in the [CUTLASS Documentation](CUTLASS.md) and the accompanying
CUTLASS 1.2 is described in the [CUTLASS Documentation](CUTLASS.md) and the accompanying
[Doxygen documentation](https://nvidia.github.io/cutlass).
We describe the structure of an efficient GEMM in our talk at the
[GPU Technology Conference 2018](http://on-demand.gputechconf.com/gtc/2018/presentation/s8854-cutlass-software-primitives-for-dense-linear-algebra-at-all-levels-and-scales-within-cuda.pdf).
# What's New in CUTLASS 1.2
_October 2018_
* [Parallelized Reductions](CUTLASS.md#parallel-reductions-across-gemm-k)
* Batched strided WMMA GEMM
# What's New in CUTLASS 1.1
_September 2018_
* [CUTLASS Documentation](CUTLASS.md)
* [Examples](examples/)