Multi-threaded Code Optimization via Contention Analysis
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Solution Overview
Problem
Traditional compilers, including JIT compilers, are thread-oblivious and optimize code primarily for single-threaded execution, failing to effectively increase the aggregate throughput of multi-threaded applications in highly concurrent environments.
Innovation Solution
A system that dynamically optimizes code by analyzing resource contention between threads, identifying critical sections, and recompiling them to produce optimized code, employing techniques like inlining, de-coarsening, and shifting computations out of critical sections to reduce lock contention and improve overall throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional JIT compilers optimize code for single-threaded execution, then the latency of individual threads is improved, but the aggregate throughput of multi-threaded applications deteriorates
Solution Approach 1:
The patent segments the optimization process by identifying and separately optimizing critical sections that are contended by multiple threads. Instead of treating the entire codebase uniformly, the system divides it into hot paths and critical sections, applying targeted optimizations to regions that cause thread contention while leaving other regions unchanged. This segmentation allows the system to improve aggregate throughput by focusing optimization efforts where they have the most impact on multi-threaded performance.
Solution Approach 2:
The patent applies local quality by making different parts of the code have different optimization characteristics. Critical sections that are heavily contended receive aggressive optimizations such as inlining and loop unrolling, while non-critical sections maintain their original characteristics. The system also applies different optimization strategies to different threads based on their contention patterns, allowing each thread to be optimized according to its specific access patterns and contention levels.
2Speed
If code is optimized to shorten the path length for single-threaded execution, then the execution speed of individual threads increases, but the lock contention in critical sections increases
Solution Approach 1:
The patent applies preliminary action by performing optimizations on critical sections before threads execute them. The system identifies hot paths and critical sections through profiling, then pre-optimizes these regions by inlining lock acquisition paths, removing biased locking admission code, and hoisting code out of critical sections. This preliminary optimization reduces the time threads spend in critical sections, thereby reducing lock contention before it becomes a problem.
Solution Approach 2:
The patent extracts harmful elements from the code by removing lock acquisition and release operations from critical sections where possible. Through techniques like hoisting code out of critical sections and inlining lock paths, the system separates the essential computation from the synchronization overhead. This extraction reduces the time threads spend waiting for locks while maintaining the correctness of the critical section semantics.
3Device complexity
If traditional compilers are used without thread-aware policies, then the code size is reduced and compilation is simpler, but the aggregate throughput of multi-threaded applications is not improved
Solution Approach 1:
The patent implements feedback by using runtime profiling information to guide compilation decisions. The system profiles application execution to identify hot paths and critical sections, then uses this feedback to trigger targeted optimizations. The feedback loop continues by monitoring the performance impact of optimizations and adjusting subsequent compilation decisions accordingly. This feedback-driven approach allows the system to achieve throughput improvements without requiring complex static analysis of all possible execution paths.
Data Source
AI summary
In modern multi-threaded environments, threads often work cooperatively toward providing collective or aggregate throughput for an application as a whole. Optimizing in the small for “thread local” common path latency is often but not always the best approach for a concurrent system composed of multiple cooperating threads. Some embodiments provide a technique for augmenting traditional code emission with thread-aware policies and optimization strategies for a multi-threaded application. During operation, the system obtains information about resource contention between executing threads of the multi-threaded application. The system analyzes the resource contention information to identify regions of the code to be optimized. The system recompiles these identified regions to produce optimized code, which is then stored for subsequent execution.