Static Verification of GPU Kernels via Symbolic Encoding
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Solution Overview
Problem
Software developers face challenges in ensuring portable correctness and preventing execution errors in GPU kernels, particularly due to data races and barrier divergence, which can lead to nondeterministic behavior and incorrect results in applications like media processing and medical imaging.
Innovation Solution
A system that includes a symbolic encoding component for static verification of data parallel program instructions, using predicated execution to obtain symbolic encodings and verify attributes such as race freedom and divergence freedom, enabling compile-time verification of GPU kernels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static verification of data parallel program instructions is performed to ensure race freedom and divergence freedom, then reliability of GPU kernel execution is improved, but device complexity increases due to the need for symbolic encoding components and verification systems
Solution Approach 1:
The system performs static verification of data parallel program instructions before execution by obtaining symbolic encodings of predicated execution and verifying attributes such as race freedom and divergence freedom. This preliminary verification ensures execution correctness while maintaining portability across different GPU accelerators, resolving the contradiction by catching errors before runtime without requiring complex runtime verification mechanisms
2Stability of the object's composition
If symbolic encoding and static verification are implemented to prevent data races and barrier divergence, then execution determinism is improved, but manufacturing precision requirements increase for the verification system
Solution Approach 1:
The system replaces traditional mechanical or hardware-based verification approaches with a software-based symbolic encoding and static verification mechanism. By using symbolic representations of predicated execution and automated verification of race freedom and divergence freedom, the system achieves high execution determinism without requiring precision-critical hardware modifications, thus resolving the contradiction between determinism and manufacturing precision requirements
Data Source
AI summary
A symbolic encoding of predicated execution for static verification, based on a plurality of data parallel program instructions, is obtained. A result of static verification of one or more attributes associated with the plurality of data parallel program instructions is obtained, based on the symbolic encoding.