Presentation
SIGN IN TO VIEW THIS PRESENTATION Sign In
Precision and Performance Analysis of C Standard Math Library Functions on GPUs
DescriptionWith the advent of GPU computing, executing large program sections on accelerators has become increasingly important. Efforts are being made to support the C standard library, LIBC, on GPUs via LLVM machinery. Therefore, the C standard math library, LIBM, must be supported on GPUs. So far, LLVM frontends, such as Clang, have relied on GPU vendor implementations of LIBM functionality wrapped into (mostly) LIBM-compatible forwarding functions.
We propose a novel LIBM for GPUs reusing a collection of LLVM target-agnostic implementations and built-ins alongside vendor implementations of most single and double-precision floating point math functions. Our approach allows selecting between individual implementations based on the GPU target as opposed to the current approach, which serves only the single third-party library implementation. Our extensive numerical analysis highlights the various implementations' differences in performance and precision. Our solution allows users to choose the implementation that maximizes speed while meeting their specific precision requirements.
We propose a novel LIBM for GPUs reusing a collection of LLVM target-agnostic implementations and built-ins alongside vendor implementations of most single and double-precision floating point math functions. Our approach allows selecting between individual implementations based on the GPU target as opposed to the current approach, which serves only the single third-party library implementation. Our extensive numerical analysis highlights the various implementations' differences in performance and precision. Our solution allows users to choose the implementation that maximizes speed while meeting their specific precision requirements.
Event Type
Workshop
TimeSunday, 12 November 202311am - 11:30am MST
Location601
Compilers
Heterogeneous Computing
Performance Optimization
W