Presentation
RedSan: A Redundant Memory Instruction Sanitizer for GPU Programs
SessionPerformance: Analysis Tools
DescriptionCUDA is the de facto programming model for GPUs, widely used in the domains of HPC and AI. To obtain bare-metal performance, vendors and academics develop various profiling tools to guide optimization. However, most existing tools focus on hotspot analysis with limited capabilities in identifying actionable opportunities. To complement existing tools, we present RedSan, a novel profiling tool that leverages binary instrumentation to identify redundant instructions in fully optimized CUDA programs. Guided by RedSan, we are able to optimize programs such as PolybenchGPU, Rodinia, PASTA, DARKNET, and LULESH, yielding up to a 6.27× speedup and 3.00× reduction in memory instructions.
Event Type
Paper
TimeTuesday, 18 November 20252:15pm - 2:37pm CST
Location263-264
Performance Measurement, Modeling, & Tools