• NVIDIA Ampere Architecture features
  • Fast Tensor Core operations:
  • Maximum performance via mma.sync
  • Tensor Float 32, BFloat16, and double-precision data types
  • Mixed integer data types (int8, int4, bin1)
  • Asynchronous copy for deep software pipelines via cp.async
  • Described in GTC 2020 Webinar (SR 21745) (free registration required)
• Features:
  • SDK examples showing GEMM fused with bias+relu and fused GEMM+GEMM
  • Complex-valued GEMMs targeting NVIDIA Ampere Tensor Cores in double-precision and Tensor Float 32
  • Gaussian complex GEMMs using 3m complex multiply algorithm
  • Universal GEMM kernel supporting two batch modes and two algorithms for parallel reductions
• Policy updates:
  • CUDA 11 Toolkit needed to enable NVIDIA Ampere Architecture features
  • Disabled F16C by default for compatibility - enable on cmake command line with -DCUTLASS_ENABLE_F16C=ON