Matrix Tile Processing for Lower-Overhead Dot Products
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Solution Overview
Problem
Handling large matrices in mainstream processors is a difficult and instruction-intensive task, especially when rows of a matrix need to be loaded into multiple packed data registers and scattered back to memory, which is inefficient for larger matrices.
Innovation Solution
Implementing mechanisms to support matrix operations in computer hardware using 2-dimensional data structures called tiles, which are acted upon by various operations such as multiplication, addition, and dot products, and are configured using the TILECONFIG instruction to optimize storage and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If rows of a matrix are loaded into multiple packed data registers and scattered back to memory, then the matrix operation can be performed, but the process becomes inefficient for larger matrices due to increased instruction overhead
Solution Approach 1:
The patent divides large matrices into smaller tile segments that can be processed efficiently. Each tile is a compact data structure that fits within the processor's register file, eliminating the need for repeated memory loading and scattering operations. The matrix operation is segmented into tile-level operations that reduce instruction overhead while maintaining computational capability.
Solution Approach 2:
The patent introduces a new data organization dimension by using 2D tile structures instead of traditional 1D vector registers. This dimensional change allows tiles to be stored and processed in a way that exploits spatial locality and reduces the number of memory operations required, thereby improving efficiency without increasing instruction complexity.
2Productivity
If traditional matrix operations are used in mainstream processors, then compatibility is maintained, but performance deteriorates due to difficulty in handling large matrices
Solution Approach 1:
The patent creates a universal tile data structure that can represent matrices of various sizes and can be operated on using standardized tile operations. This multi-functional approach allows the same hardware circuitry and instruction set to efficiently handle different matrix dimensions without requiring complex operation-specific code, thereby improving performance while maintaining ease of operation.
Solution Approach 2:
The patent changes the fundamental parameters of matrix representation from traditional row-major or column-major storage in linear registers to 2D tile structures with specific dimensions. This parameter change enables more efficient memory access patterns and reduces the computational overhead associated with traditional matrix operations on large datasets.
Data Source
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AI summary
Embodiments detailed herein relate to matrix operations. For example, an apparatus comprises programmable configuration storage, decode circuitry and execution circuitry. The programmable configuration storage is to store configuration information for a first matrix, a second matrix, and a third matrix, the configuration information including a first value corresponding to a first number of rows for the first matrix, a second value corresponding to a second number of columns for the first matrix, a third value corresponding to a third number of rows for the second matrix, a fourth value corresponding to a fourth number of columns for the second matrix, a fifth value corresponding to a fifth number of rows for the third matrix, a sixth value corresponding to the sixth number of columns for the third matrix, and a start row value corresponding to a row of a corresponding matrix at which to restart execution of at least one of a plurality of matrix instructions. The decode circuitry is to decode the plurality of matrix instructions, including a single instruction to perform dot-product and accumulation, the single instruction having a first operand to specify a first register, a second operand to specify a second register, and a third operand to specify a third register. The execution circuitry is to perform one or more operations corresponding to the single instruction, including: performing dot-products on elements of the second matrix from the second register and elements of the third matrix from the third register to generate one or more resulting elements, and accumulating the one or more resulting elements into the first matrix in the first register.