Virginia Madsen
Search results
CUTLASS 3.5 - April 2024. CUTLASS is a collection of CUDA C++ template abstractions for implementing high-performance matrix-matrix multiplication (GEMM) and related computations at all levels and scales within CUDA. It incorporates strategies for hierarchical decomposition and data movement similar to those used to implement cuBLAS and cuDNN.
A cutlass is a short, broad sabre or slashing sword, with a straight or slightly curved blade sharpened on the cutting edge, and a hilt often featuring a solid cupped or basket-shaped guard. It was a common naval weapon during the early Age of Sail .
The Oldsmobile Cutlass was a series [1] of automobiles produced by General Motors ' Oldsmobile division between 1961 and 1999. At its introduction, the Cutlass was Oldsmobile's entry-level model; it began as a unibody compact car, but saw its greatest success as a body-on-frame intermediate.
- 1961–1999
May 21, 2018 · CUTLASS is very efficient, with performance comparable to cuBLAS for scalar GEMM computations. Figure 9 shows CUTLASS performance relative to cuBLAS compiled with CUDA 9.0 running on an NVIDIA Tesla V100 GPU for large matrix dimensions ( M =10240, N = K =4096).
Apr 11, 2024 · CUTLASS 3.5.0 Latest. Implicit GEMM Convolutions targeting Hopper SM90A via WGMMA + TMA im2col . Native implementation in CUTLASS 3.x using CuTe, mirroring the same design hierarchy as that of GEMMs. Support for 1D, 2D, and 3D convolutions in a rank-agnostic fashion. Support for Fprop, Dgrad, and Wgrad algorithms.
People also ask
What is Cutlass C++?
What is Cutlass GEMM?
How efficient is Cutlass compared to cublas?
What is Cutlass 3?
Apr 12, 2024 · CUTLASS 3.5 - April 2024. CUTLASS is a collection of CUDA C++ template abstractions for implementing high-performance matrix-matrix multiplication (GEMM) and related computations at all levels and scales within CUDA. It incorporates strategies for hierarchical decomposition and data movement similar to those used to implement cuBLAS and cuDNN.
Nov 23, 2021 · 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.
