tilelang.carver.arch.cuda

Classes

CUDA

Represents the architecture of a computing device, capturing various hardware specifications.

Functions

Module Contents

tilelang.carver.arch.cuda.is_cuda_arch(arch)
参数:

arch (tilelang.carver.arch.arch_base.TileDevice)

返回类型:

bool

tilelang.carver.arch.cuda.is_volta_arch(arch)
参数:

arch (tilelang.carver.arch.arch_base.TileDevice)

返回类型:

bool

tilelang.carver.arch.cuda.is_ampere_arch(arch)
参数:

arch (tilelang.carver.arch.arch_base.TileDevice)

返回类型:

bool

tilelang.carver.arch.cuda.is_ada_arch(arch)
参数:

arch (tilelang.carver.arch.arch_base.TileDevice)

返回类型:

bool

tilelang.carver.arch.cuda.is_hopper_arch(arch)
参数:

arch (tilelang.carver.arch.arch_base.TileDevice)

返回类型:

bool

tilelang.carver.arch.cuda.has_mma_support(arch)
参数:

arch (tilelang.carver.arch.arch_base.TileDevice)

返回类型:

bool

tilelang.carver.arch.cuda.is_tensorcore_supported_precision(in_dtype, accum_dtype, arch)
参数:
返回类型:

bool

class tilelang.carver.arch.cuda.CUDA(target)

Bases: tilelang.carver.arch.arch_base.TileDevice

Represents the architecture of a computing device, capturing various hardware specifications.

参数:

target (tvm.target.Target | str)

target
sm_version
name
device: tvm.runtime.Device
platform: str = 'CUDA'
smem_cap
compute_max_core
warp_size
compute_capability
reg_cap: int = 65536
max_smem_usage: int
sm_partition: int = 4
l2_cache_size_bytes: int
transaction_size: list[int] = [32, 128]
bandwidth: list[int] = [750, 12080]
available_tensor_instructions: list[TensorInstruction] = None
get_avaliable_tensorintrin_shapes()
__repr__()