MMA Datapath Parallel Dot Products With Lower Register Bandwidth
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional processors inefficiently perform matrix multiply and accumulate operations due to the need to break them down into basic arithmetic operations using scalar operands, leading to excessive use of register file bandwidth and inefficient data movement.
Innovation Solution
A processor datapath is designed to execute matrix multiply and accumulate operations by generating dot products of vector operands, utilizing operand collectors to store data temporarily and reducing the need for repeated loading from the register file, allowing parallel execution of multiple elements of the result matrix.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If matrix multiply accumulate operations are broken down into basic arithmetic operations using scalar operands, then the processor can use existing hardware logic to perform operations, but the register file bandwidth is excessively consumed and data movement becomes inefficient
Solution Approach 1:
The patent segments the matrix operation into dot product operations that can be executed in parallel. By breaking down the matrix multiply accumulate into multiple independent dot product computations, the system can process multiple elements simultaneously, improving productivity while maintaining hardware simplicity
Solution Approach 2:
The patent introduces a new dimension of parallel execution by processing multiple dot product operations simultaneously across different data elements. This dimensional approach to parallelization allows the system to overcome the bandwidth limitations of sequential scalar operations without requiring complex hardware modifications
2Ease of manufacture
If matrix operations are executed using sequential basic arithmetic operations, then hardware logic can be utilized, but processing speed is reduced due to sequential execution requirements
Solution Approach 1:
The patent performs preliminary actions by loading and preparing multiple data elements into registers before executing the dot product operations. This preliminary data preparation enables subsequent parallel execution of multiple dot product operations, significantly increasing processing speed while using standard hardware arithmetic logic
Solution Approach 2:
The patent maintains continuity of useful action by executing multiple dot product operations in parallel without idle cycles. The system continuously processes multiple elements simultaneously, maximizing hardware utilization and processing speed through sustained parallel computation
3Ease of operation
If data is repeatedly loaded from register file for each basic arithmetic operation, then operations can be performed, but register file bandwidth is excessively consumed
Solution Approach 1:
The patent loads all required data elements into registers in advance before executing the dot product operations. This preliminary data loading action ensures that subsequent arithmetic operations can proceed without repeated register file accesses, dramatically reducing the volume of data movement while maintaining ease of operation execution
Solution Approach 2:
The patent uses registers as intermediary storage to hold data elements during the computation process. By keeping multiple data elements in registers simultaneously, the system eliminates the need for repeated register file bandwidth consumption, using the register file only for initial data loading and final result storage
Data Source
AI summary
A method, computer readable medium, and processor are disclosed for performing matrix multiply and accumulate (MMA) operations. The processor includes a datapath configured to execute the MMA operation to generate a plurality of elements of a result matrix at an output of the datapath. Each element of the result matrix is generated by calculating at least one dot product of corresponding pairs of vectors associated with matrix operands specified in an instruction for the MMA operation. A dot product operation includes the steps of: generating a plurality of partial products by multiplying each element of a first vector with a corresponding element of a second vector; aligning the plurality of partial products based on the exponents associated with each element of the first vector and each element of the second vector; and accumulating the plurality of aligned partial products into a result queue utilizing at least one adder.