ttnn.MatmulMultiCoreReuseMultiCastDRAMShardedProgramConfig
- class ttnn.MatmulMultiCoreReuseMultiCastDRAMShardedProgramConfig
-
Bases:
pybind11_objectThis program config is a specialized config for very narrow tensors stored in DRAM.
- from_json(self: str) ttnn._ttnn.operations.matmul.MatmulMultiCoreReuseMultiCastDRAMShardedProgramConfig
- property fused_activation
-
Optional fused activation function to apply during computation.
If specified, the activation function is applied directly during the DRAM-sharded matmul operation. This can provide significant performance benefits by avoiding additional memory round-trips in DRAM-based operations.
- property in0_block_w
-
Block width for both input tensors along the K dimension (shared inner dimension).
Determines the data granularity by specifying how many tiles wide each block is along the inner dimension for both input_tensor_a and input_tensor_b in DRAM-sharded operations. This parameter must be chosen to align with the DRAM sharding strategy and optimize memory bandwidth utilization for both tensors.
- property per_core_M
-
Number of output tiles each core processes along the M dimension.
Determines how the M dimension is distributed across cores in DRAM-sharded scenarios. This must align with the DRAM sharding pattern to ensure optimal performance and avoid memory access conflicts.
- property per_core_N
-
Number of output tiles each core processes along the N dimension.
Determines how the N dimension is distributed across cores in DRAM-sharded scenarios. This parameter affects the multicast efficiency and must be compatible with the DRAM sharding configuration.