CUTLASS 2.8

• TF32x3: emulated single-precision using Tensor Cores

  • 45+ TFLOPs on NVIDIA A100
  • GEMM SDK example (real)
  • COMPLEX GEMM SDK example (complex)
  • Implicit GEMM Convolution SDK example

• Mainloop fusion for Convolution: convolution with fused per-channel scale-bias-relu

  • Conv Fprop SDK example
  • Conv WGrad SDK example
  • cutlass::conv::device::ImplicitGemmConvolutionFusion

• Grouped GEMM: similar to batched GEMM with distinct problem size per group

  • SDK example with performance comparison with Batched Strided GEMM
  • cutlass::gemm::device::GemmGrouped

• Implicit GEMM Convolution fusion supports staging 1st convolution's output accumulator in the shared memory on Turing. This allows more flexible warp tile sizes and less regsiter pressue.

• Optimal performance using CUDA 11.5

• Updates from the community (thanks!)

• Deprecation announcement: CUTLASS plans to deprecate the following:

  • Maxwell and Pascal GPU architectures
  • Ubuntu 16.04
  • CUDA 10.2