Shader Profiler for GPU Execution Time Analysis
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Solution Overview
Problem
Current methods lack effective means to accurately monitor and optimize shader program execution performance in graphics processing units (GPUs), which is crucial for efficient graphics operations in portable devices, as inefficient shader operations significantly impact overall program behavior.
Innovation Solution
A shader profiling technique that captures and analyzes GPU API traces to determine the execution time of each source code instruction, providing a GPU time cost and percentage associated with each source line, allowing programmers to improve code efficiency by analyzing execution time line by line.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If shader program execution is monitored using traditional methods, then some performance data can be obtained, but the measurement precision is insufficient to accurately identify time-consuming instructions
Solution Approach 1:
The shader program execution is segmented into individual instructions, with each instruction's execution time measured separately. The profiler divides the shader code into basic blocks and tracks the start and end times of each instruction, enabling precise identification of time-consuming operations without measuring the entire program as a single unit.
Solution Approach 2:
A profiler intermediary component is introduced between the shader execution and the monitoring system. This profiler captures execution events, records timestamps, and processes timing data without interfering with the actual shader execution, providing accurate measurements while maintaining system separation.
2Productivity
If detailed timing information is collected for each instruction, then execution efficiency can be optimized, but the loss of time for data collection and processing increases
Solution Approach 1:
The profiler performs preliminary actions by pre-compiling shader code with instrumentation that inserts timing markers at key instruction points. This preparation is done once before execution, so that during actual runtime, only simple timestamp recordings are needed, minimizing the overhead during performance-critical execution phases.
Solution Approach 2:
The system changes the parameter of measurement granularity by offering different profiling modes. In lightweight mode, only aggregate timing for shader stages is recorded. In detailed mode, individual instruction timing is captured. This allows users to balance between profiling accuracy and overhead based on specific optimization needs.
3Measurement precision
If the profiler captures complete execution traces, then accurate performance analysis is achieved, but the device complexity and memory requirements increase
Solution Approach 1:
The profiler extracts only the essential timing information from complete execution traces. Instead of storing full trace data including all intermediate states and debug information, it selectively extracts start and end timestamps for each instruction, removing unnecessary data while preserving the core performance metrics needed for analysis.
Solution Approach 2:
The system implements partial profiling by default, capturing timing data for only the most critical shader stages and instructions. Users can enable detailed tracing of all instructions when absolutely necessary, but the default configuration focuses on the subset of data that provides the most value for performance optimization, reducing memory usage while maintaining practical utility.
Data Source
AI summary
Systems, methods, and computer readable media to improve the development of image processing intensive programs are described. In general, techniques are disclosed to non-intrusively monitor the run-time performance of shader programs on a graphics processing unit (GPU)—that is, to profile shader program execution. More particularly, the shader profiling comprises of sampling data during the execution of a compiled code on GPU. The execution duration of the sequences of instructions within the code is determined. Subsequently, based relative latency of the instructions within the sequence, the duration time for each binary instruction is determined. The binary instructions are then mapped to source code in order to obtain the amount of time each source code instruction in a shader take to execute per draw call.