🚀 Master GPU Performance on Modal!
@charles_irl @modal_labs
🖥️ Optimize for High-Performance Computing: With powerful and costly GPUs like the H100, maximizing efficiency is crucial—especially for demanding ML tasks needing 10x CPU efficiency.
🔍 Profiling Essentials: Start with GPU utilization checks using Nvidia SMI, then examine power usage to confirm full utilization.
📊 Reduce CPU Bottlenecks: Avoid redundant Python calls in loops that slow down GPU tasks; PyTorch’s profiler can reveal these inefficiencies.
🎛️ Powerful Tools: Use TensorBoard, Perfetto, and PyTorch profiling on Modal for detailed insights into SM efficiency, kernel utilization, and more.
🌡️ Monitor Power & Temperature: Keep an eye on these metrics to prevent overheating and prolong hardware life.
🚀 Scale Workloads Smartly: Optimize by increasing batch sizes or input counts to fully utilize GPU resources.
💾 Leverage Modal Storage: Store profiling outputs remotely to access insights across instances and streamline team workflows.
🔄 Iterative Optimization: Continuously profile, trace, and adjust workloads to achieve the best latency and throughput.
#GPUOptimization #MLPerformance #HighPerformanceComputing #ModalPlatform