FPChecker: Detecting Floating-Point Exceptions in GPU Applications
Ignacio Laguna · 2019
Floating-point arithmetic is widely used in applications from several fields including scientific computing, machine learning, graphics, and finance. Many of these applications are rapidly adopting the use of GPUs to speedup computations. GPUs, however, have limited support to detect floating-point exceptions, which hinders the development of reliable applications in GPU-based systems. We present FPCHECKER, the first tool to automatically detect floating-point exceptions in GPU applications. FPCHECKER uses the clang/LLVM compiler to instrument GPU kernels and to detect exceptions at runtime. Once an exception is detected, it reports to the programmer the code location of the exception as well as other useful information. The programmer can then use this report to avoid the exception, e.g., by modifying the application algorithm or changing the input. We present the design of FPCHECKER, an evaluation of the overhead of the tool, and a real-world case scenario on which the tool is used to identify a hidden exception. The slowdown of FPCHECKER is moderate and the code is publicly available as open source.