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Mojo module

mha_utils

Shared configuration types and dispatch helpers for MHA GPU kernels.

Provides MHAConfig (tile/pipeline configuration), FlashAttentionAlgorithm (algorithm variant selector), mask-dispatch helpers, and partition-scheme types used by both prefill and decode attention kernels.

comptime values

callback_fn_type

comptime callback_fn_type = def[mask_t: MHAMask](mask: mask_t) raises capturing thin -> None

is_sm100

comptime is_sm100 = (StringSpan("sm_100") in String(_accelerator_arch())) or (StringSpan("sm_103") in String(_accelerator_arch()))

is_sm90

comptime is_sm90 = (StringSpan("sm_90") in String(_accelerator_arch()))

is_sm90or100

comptime is_sm90or100 = is_sm90 or is_sm100

MHA_PDL_LEVEL

comptime MHA_PDL_LEVEL = PDLLevel.OVERLAP_AT_END if get_defined_bool[StringSpan("MHA_PDL"), True]() else PDLLevel.OFF

Structs

• ​DynamicInt: A runtime integer value that satisfies OptionallyStaticInt.
• ​FlashAttentionAlgorithm: Identifies which flash-attention algorithm variant to use for a kernel launch.
• ​MHAConfig: Compile-time and runtime tile-shape configuration for MHA GPU kernels.
• ​NoPartition: A single-partition (non-split-K) scheme for MHA decoding.
• ​SplitKPartition: A multi-partition split-K scheme for MHA decoding over long sequences.
• ​StaticInt: A compile-time constant integer that satisfies OptionallyStaticInt.

Traits

• ​MHAPartitionScheme: Trait describing how the key-value sequence is partitioned for split-K decoding.
• ​OptionallyStaticInt: Trait for integer values that may be statically known at compile time.

Functions

• ​as_dynamic_row_major_1d: Reinterprets a generic-address LayoutTensor as a 1-D dynamic row-major tensor.
• ​dispatch_mask: Instantiate an MHAMask by name and invoke a callback with it.
• ​dispatch_materialized_mask: Wrap a dense mask tensor in a MaterializedMask and invoke a callback.
• ​get_start_and_end_for_partitions: Calculate start and end indices for a partition.