Tracing JIT Compiler Parallelization via Runtime Trace Analysis
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Solution Overview
Problem
Language compilers face challenges in determining whether to parallelize loops due to insufficient information about loop dependencies, leading to conservative approaches that fail to expedite program execution effectively.
Innovation Solution
A tracing just-in-time (TJIT) compiler system that extracts trace information during runtime to identify parallelizable operation components and allocates them to processing resources, using predicate and access information to determine safety and feasibility of parallelization, with the assistance of a theorem prover module for logical analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a language compiler performs static compile-time parallelization of loops, then code execution can be expedited through parallel processing, but the compiler lacks sufficient information to determine whether parallelization is safe or worthwhile
Solution Approach 1:
The system performs preliminary runtime analysis by executing loop iterations and tracing their execution paths before making parallelization decisions. This preliminary action collects information about loop dependencies and execution characteristics that are unavailable during static compilation, enabling informed parallelization decisions while maintaining execution efficiency.
Solution Approach 2:
The system implements feedback mechanisms where runtime execution data from traced loop iterations is fed back to the compiler system. This feedback provides actual dependency information and execution patterns, allowing the compiler to make accurate parallelization decisions based on real runtime behavior rather than static analysis alone.
2Reliability
If the language compiler takes a conservative approach to parallelization due to insufficient information, then parallelization safety is maintained, but significant gains in execution expediting are failed
Solution Approach 1:
The system transitions from static compile-time decisions to dynamic runtime decisions for parallelization. By continuously monitoring loop execution characteristics and dependencies during runtime, the system can dynamically adjust parallelization strategies, achieving both safety through accurate dependency detection and productivity through aggressive parallelization when conditions permit.
Solution Approach 2:
The system changes the informational parameters available to the compiler by collecting runtime execution data. This parameter change provides concrete information about loop dependencies, iteration patterns, and resource usage, enabling the compiler to move from conservative defaults to optimized parallelization decisions that maintain safety while maximizing execution speedup.
3Measurement precision
If the TJIT compiler system extracts and analyzes trace information during runtime, then accurate parallelization decisions can be made, but additional runtime overhead is introduced
Solution Approach 1:
The system applies partial action by selectively tracing and analyzing only the loop iterations that are actually executed during runtime, rather than analyzing all possible iterations. This partial approach collects sufficient dependency information with minimal overhead, enabling accurate parallelization decisions without the excessive cost of comprehensive analysis of unreachable or redundant iterations.
Data Source
AI summary
A tracing just-in-time (TJIT) compiler system is described for performing parallelization of code in a runtime phase in the execution of code. Upon detecting a hot loop during the execution of the code, the compiler system extracts trace information from sequentially recorded traces. In a first phase, the compiler system uses the trace information to identify at least one group of operation components that can be operated on in a parallel manner. In a second phase, the compiler system provides instructions which allocate the group of operation components to plural processing resources. A native code generator module carries out those instructions by recompiling native code that directs the operation of a native system to perform parallel processing. The compiler system terminates a group if it encounters program data in a loop iteration that is not consistent with previously encountered predicated information (upon which it records a new trace in a sequential manner).