Predicated Vector Instruction Micro-operation Composition
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Solution Overview
Problem
In data processing systems that support vector instructions, the generation of fixed micro-operations for predicated vector instructions, regardless of the predicate value, can lead to inefficient usage of processing hardware due to the presence of many inactive data elements, resulting in unnecessary resource utilization and energy consumption.
Innovation Solution
The instruction decoding circuitry reads or predicts the estimated predicate value at the decode stage to vary the composition of micro-operations, allowing for more efficient use of processing hardware by adjusting the vector size, number of micro-operations, or fusing instructions based on the sparsity of active elements, thereby optimizing resource utilization and power savings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fixed micro-operations are generated for predicated vector instructions regardless of predicate value, then the instruction decoding is simple and fast, but processing hardware resources are wasted due to inactive data elements
Solution Approach 1:
The micro-operation composition is made dynamic by adjusting it based on the estimated predicate value. The instruction decoding circuitry varies the composition of micro-operations depending on whether active data elements are sparse or dense, transitioning from a static fixed composition approach to a dynamic adaptive approach that optimizes resource utilization and energy consumption based on runtime conditions
Solution Approach 2:
The system changes parameters of micro-operations (such as vector length, number of operations) based on the estimated predicate value. When active elements are sparse, the system reduces vector size and number of micro-operations, effectively changing operational parameters to match the actual workload and reduce energy consumption
2Productivity
If the composition of micro-operations is varied based on estimated predicate value, then resource utilization is improved, but the complexity of instruction decoding increases
Solution Approach 1:
The system performs preliminary estimation of the predicate value at the instruction decoding stage, before full execution. This preliminary action allows the system to pre-determine the appropriate micro-operation composition, avoiding the need for complex runtime adjustments during execution and distributing complexity to an earlier, more efficient stage
Solution Approach 2:
An estimated predicate value acts as an intermediary between the instruction and the micro-operation generation. This intermediary provides guidance information that simplifies the decoding process by enabling conditional selection of micro-operation compositions without requiring complex analysis of the actual predicate value at execution time
3Power
If vector operations are performed on all data elements regardless of predicate value, then the hardware can operate at full capacity, but energy is wasted on inactive elements
Solution Approach 1:
The system extracts and processes only the necessary subset of data elements based on the estimated predicate value. When active elements are sparse, it extracts and processes only those specific elements rather than all elements, removing the waste of processing power on inactive elements while maintaining full utilization of processing power on the relevant subset
Data Source
AI summary
An apparatus comprises instruction decoding circuitry to generate micro-operations in response to program instructions; and processing circuitry to perform data processing in response to the micro-operations generated by the instruction decoding circuitry. In response to a predicated vector instruction, the instruction decoding circuitry reads or predicts an estimated value of the predicate value, and depending on the estimated value, varies a composition of at least one micro-operation generated in response to the predicated vector instruction. This can enable more efficient use of hardware resources in the processing circuitry.