Eliminating Partial-Redundant Vector Loads in Compiler Optimization
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Solution Overview
Problem
Current compiler optimization techniques, such as partial redundancy elimination, are ineffective in eliminating partial-redundant vector loads, which occur when only a portion of vector elements overlap, leading to inefficient performance in vectorized code, particularly in stencil computations used in scientific and engineering applications.
Innovation Solution
The method involves detecting and replacing groups of partial-redundant vector loads with a smaller set of non-redundant or reduced-redundant vector loads by grouping vector operations based on common characteristics, applying transformation limitations, and using instructions like (V)PALIGN* to reduce memory accesses, thereby optimizing code performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If vectorization is enabled to process multiple data elements in parallel, then execution speed is improved, but memory access redundancy increases leading to performance degradation
Solution Approach 1:
The patent extracts and eliminates redundant vector load operations from the code. The optimization technique identifies partial-redundant vector loads where only some elements are actually needed, and removes the unnecessary load operations, keeping only the essential memory accesses required for correct execution.
Solution Approach 2:
The patent changes the parameters of vector operations by introducing vector shuffle operations and modifying load patterns. Instead of loading complete vectors when only partial data is needed, the optimization transforms the code to load smaller amounts of data and use vector shuffle instructions to rearrange elements, thereby reducing memory bandwidth consumption.
2Ease of operation
If partial-redundant vector loads are executed to maintain simplicity in code structure, then ease of operation is preserved, but productivity decreases due to inefficient memory accesses
Solution Approach 1:
The patent introduces dynamic optimization by analyzing runtime characteristics of vector operations. The system dynamically identifies patterns of partial redundancy and applies different optimization strategies based on the specific characteristics of each vector load operation, adapting the code transformation to the actual usage patterns.
Solution Approach 2:
The patent introduces vector shuffle operations as intermediary steps between memory loads and computational operations. These shuffle operations act as mediators that rearrange vector elements to match the actual data requirements, allowing the compiler to eliminate redundant loads while maintaining correct program semantics.
3Reliability
If multiple vector loads are performed to ensure data availability, then reliability is improved, but loss of time increases due to redundant memory accesses
Solution Approach 1:
The patent performs preliminary analysis of vector operations to identify which elements will actually be used in subsequent computations. By determining the exact data requirements in advance, the optimization can pre-load only the necessary elements, avoiding redundant memory accesses that would waste time without providing any benefit to data availability.
Data Source
AI summary
Methods, apparatus, systems and articles of manufacture are disclosed to eliminate partial-redundant vector load operations. An example apparatus includes a node grouper to associate a vector operation with a node group, a candidate verifier to perform a dependencies test on a subset of the node group, and identify a subset of the node group as a candidate when the subset satisfies the dependencies test, and a code optimizer to determine replacement code based on a characteristic of the candidate in the node group and compare an estimated cost associated with executing the replacement code to a threshold. The example apparatus also includes a code generator to generate machine code using the replacement code when the estimated cost of executing the replacement code satisfies the threshold.