NVIDIA/cutlass v2.6.0

CUTLASS 2.6.0

on GitHub

CUTLASS 2.6.0

• Optimal performance when compiled with the CUDA 11.4 Toolkit
  • Adopt the new L2 prefetch feature in cp.async and global load
• Fused operators with GEMM and Convolution
  • Fused broadcast in epilogue
  • Fused partial reduction in epilogue
• 64b tensor strides and leading dimensions support for GEMMs
• Affine rank=2 matrix layouts
  • Row stride and column stride for matrices using cutlass::layout::AffineRank2
  • Support FP64 tensor core and SIMT GEMM.
• Batched GEMV preview implementation
• New strided Dgrad implementation
  • Accelerates over previous implementation by cutting down redundant math by 4x
  • Support using new Dy and w analytic iterators and existing cutlass::conv::device::ImplicitGemmConvolution interface
• Quaternion-valued GEMM and Convolution in single- and double-precision (targeting CUDA Cores)
  • Updates to quaternion.h and functional.h
  • SDK Example for GEMM and Convolution
  • Unit tests for GEMM and Convolution
• Many improvements to the epilogue.
  • Provide an option to not fully unroll the epilogue to reduce the code size and improve the performance when using complicated elementwise operations
  • Performance improvement for FP16 tensor core kernels
  • Bug fixes
• Enhanced Clang support and the combination of Clang 13 and CUDA 11.4 can build and run kernels from Pascal and Ampere.
• Updated minimum CUDA Toolkit requirement to 10.2
  • CUDA 11.4 Toolkit recommended
• Corrections and bug fixes reported by the CUTLASS community
  • Thank you for filing these issues!