We present a novel framework for debugging GPU stream programs through automatic dataflow recording and visualization. Our debugging system can help programmers locate errors that are common in general purpose stream programs but very difficult to debug with existing tools. A stream program is first compiled into an instrumented program using a compiler. This instrumenting compiler automatically adds to the original program dataflow recording code that saves the information of all GPU memory operations into log files. The resulting stream program is then executed on the GPU. With dataflow recording, our debugger automatically detects common memory errors such as out-of-bound access, uninitialized data access, and race conditions -- these errors are extremely difficult to debug with existing tools. When the instrumented program terminates, either normally or due to an error, a dataflow visualizer is launched and it allows the user to examine the memory operation history of all threads and valuesin all streams. Thus the user can analyze error sources by tracing through relevant threads and streams using the recorded dataflow.
展开▼
