Compiler Register Allocation via Performance Cost Analysis
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Solution Overview
Problem
Existing methods for modifying instructions to move data in and out of memory do not effectively consider performance costs, leading to suboptimal execution in parallel computing platforms.
Innovation Solution
A compiler analyzes potential transformations to optimize register assignment and allocation, estimating performance costs and selecting transformations to implement during compilation, thereby reducing register pressure and improving program performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If instructions are modified to move data in and out of memory, then data transfer capability is improved, but performance costs increase
Solution Approach 1:
The system changes parameters by analyzing multiple potential transformations and selecting the one with the lowest estimated performance cost. This involves evaluating different data movement strategies and their associated costs, then choosing the optimal parameter configuration that minimizes performance impact while achieving necessary data transfer.
Solution Approach 2:
The system implements feedback by measuring actual performance costs of transformations and using this information to guide future transformation decisions. The performance cost measurements feed back into the transformation selection process, allowing the system to learn and optimize its data movement strategies over time.
2Productivity
If register allocation is optimized to reduce register pressure, then execution efficiency is improved, but compilation complexity increases
Solution Approach 1:
The system performs preliminary actions by analyzing potential transformations and estimating their performance costs before actually applying them. The compiler evaluates multiple transformation options in advance, calculates their expected performance impact, and selects the optimal transformation before code generation, thereby simplifying the overall compilation process.
Solution Approach 2:
The compilation process is segmented into distinct phases: transformation analysis, performance cost estimation, transformation selection, and code generation. By dividing the complex task of register allocation optimization into manageable segments, the system can efficiently handle each phase independently while maintaining overall optimization effectiveness.
3Productivity
If transformations are applied during compilation, then program performance is improved, but number of transformations required increases
Solution Approach 1:
The system applies partial action by selecting only the most beneficial transformations rather than applying all possible transformations. By estimating performance costs and choosing transformations that provide the greatest performance improvement per transformation applied, the system avoids unnecessary transformations while still achieving significant performance gains.
Data Source
AI summary
Apparatuses, systems, and techniques to allocate and/or assign registers. In at least one embodiment, registers are allocated based, at least in part, on a set of estimated performance metrics associated with transformations generated prior to a register allocation phase of compilation.