FullAIEMLTable.md

AIE-ML Development See Vitis™ Development Environment on xilinx.com See Vitis™ AI Development Environment on xilinx.com

Matrix Multiplication Compute Performance of the AI Engin ML Tiles

This table summarizes IO/Compute balance for all supported input data types and matrix sizes:

• Mat A Type: number of bits of Matrix A data type. bf16is 16 bit wide.
• Mat B Type: number of bits of Matrix A data type. bf16is 16 bit wide.
• Compute (MAC/cyc): number of parallel multiplication-accumulations that can be performed by the vector processor of the AI Engine ML
• M: number of rows of matrix A
• K: number of columns of matrix A = number of rows of matrix B
• N: number of columns of matrix B
• Mat A Size B): number of bytes used to encode matrix A
• Mat B Size (B): number of bytes used to encode matrix B
• Load Mat A (cyc): number of cycles necessary to load Matrix A
• Load Mat B (cyc): number of cycles necessary to load Matrix B
• Compute (cyc): Number of cycles necessary to compute the matrix multiplication
• Compute (%): Efficiency of the vector processor usage compared to the max of IO and compute burden
• IO A (%): Efficiency of the matrix A load compared to the the max IO and compute burden
• IO B (%): Efficiency of the matrix B load compared to the the max IO and compute burden

Mat A Type	Mat B Type	Compute (MAC/cyc)	M	K	N	Mat A Size (B)	Mat B Size (B)	Load Mat A (cyc)	Load Mat B (cyc)	Compute (cyc)	Compute (%)	IO A %	IO B %
8b	4b	512	4	16	8	64	64	2	2	1	0.5	1	1
8b	4b	512	8	16	8	128	64	4	2	2	0.5	1	0.5
8b	4b	512	4	32	8	128	128	4	4	2	0.5	1	1
8b	8b	256	4	8	4	32	32	1	1	0.5	0.5	1	1
8b	8b	256	4	16	4	64	64	2	2	1	0.5	1	1
8b	8b	256	8	8	4	64	32	2	1	1	0.5	1	0.5
8b	8b	256	2	8	8	16	64	0.5	2	0.5	0.25	0.25	1
8b	8b	256	4	8	8	32	64	1	2	1	0.5	0.5	1
8b	8b	256	2	16	8	32	128	1	4	1	0.25	0.25	1
8b	8b	256	4	16	8	64	128	2	4	2	0.5	0.5	1
16b	8b	128	4	4	4	32	16	1	0.5	0.5	0.5	1	0.5
16b	8b	128	8	4	4	64	16	2	0.5	1	0.5	1	0.25
16b	8b	128	4	8	4	64	32	2	1	1	0.5	1	0.5
16b	8b	128	4	4	8	32	32	1	1	1	1	1	1
8b	16b	128	4	4	8	16	64	0.5	2	1	0.5	0.25	1
8b	16b	128	4	4	4	16	32	0.5	1	0.5	0.5	0.5	1
16b	16b	64	4	4	4	32	32	1	1	1	1	1	1
16b	16b	64	2	4	8	16	64	0.5	2	1	0.5	0.25	1
16b	16b	64	4	4	8	32	64	1	2	2	1	0.5	1
16b	16b	64	4	2	8	16	32	0.5	1	1	1	0.5	1
32b	16b	32	2	4	8	32	64	1	2	2	1	0.5	1
32b	16b	32	4	4	4	64	32	2	1	2	1	1	0.5
32b	16b	32	4	2	4	32	16	1	0.5	1	1	1	0.5
16b	32b	32	2	4	8	16	128	0.5	4	2	0.5	0.125	1
16b	32b	32	4	4	4	32	64	1	2	2	1	0.5	1
32b	32b	16	4	2	4	32	32	1	1	2	1	0.5	0.5
32b	32b	16	4	4	4	64	64	2	2	4	1	0.5	0.5
32b	32b	16	8	2	4	64	32	2	1	4	1	0.5	0.25
bf16	bf16	128	4	8	4	64	64	2	2	1	0.5	1	1

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