On Mon, Jul 29, 2024 at 1:51 AM Peter Zijlstra <peterz@xxxxxxxxxxxxx> wrote: > > On Sun, Jul 28, 2024 at 01:29:53PM -0700, Rong Xu wrote: > > Hi, > > > > This patch series is to integrate AutoFDO and Propeller support into > > the Linux kernel. AutoFDO is a profile-guided optimization technique > > that leverages hardware sampling to enhance binary performance. > > Unlike Instrumentation-based FDO (iFDO), AutoFDO offers a user-friendly > > and straightforward application process. While iFDO generally yields > > superior profile quality and performance, our findings reveal that > > AutoFDO achieves remarkable effectiveness, bringing performance close > > to iFDO for benchmark applications. Similar to AutoFDO, Propeller too > > utilizes hardware sampling to collect profiles and apply post-link > > optimizations to improve the benchmark’s performance over and above > > AutoFDO. > > > > Our empirical data demonstrates significant performance improvements > > with AutoFDO and Propeller, up to 10% on microbenchmarks and up to 5% > > on large warehouse-scale benchmarks. This makes a strong case for their > > inclusion as supported features in the upstream kernel. > > > > Background > > > > A significant fraction of fleet processing cycles (excluding idle time) > > from data center workloads are attributable to the kernel. Ware-house > > scale workloads maximize performance by optimizing the production kernel > > using iFDO (a.k.a instrumented PGO, Profile Guided Optimization). > > > > iFDO can significantly enhance application performance but its use > > within the kernel has raised concerns. AutoFDO is a variant of FDO that > > uses the hardware’s Performance Monitoring Unit (PMU) to collect > > profiling data. While AutoFDO typically yields smaller performance > > gains than iFDO, it presents unique benefits for optimizing kernels. > > > > AutoFDO eliminates the need for instrumented kernels, allowing a single > > optimized kernel to serve both execution and profile collection. It also > > minimizes slowdown during profile collection, potentially yielding > > higher-fidelity profiling, especially for time-sensitive code, compared > > to iFDO. Additionally, AutoFDO profiles can be obtained from production > > environments via the hardware’s PMU whereas iFDO profiles require > > carefully curated load tests that are representative of real-world > > traffic. > > > > AutoFDO facilitates profile collection across diverse targets. > > Preliminary studies indicate significant variation in kernel hot spots > > within Google’s infrastructure, suggesting potential performance gains > > through target-specific kernel customization. > > > > Furthermore, other advanced compiler optimization techniques, including > > ThinLTO and Propeller can be stacked on top of AutoFDO, similar to iFDO. > > ThinLTO achieves better runtime performance through whole-program > > analysis and cross module optimizations. The main difference between > > traditional LTO and ThinLTO is that the latter is scalable in time and > > memory. > > This, > > > Propeller is a profile-guided, post-link optimizer that improves > > the performance of large-scale applications compiled with LLVM. It > > operates by relinking the binary based on an additional round of runtime > > profiles, enabling precise optimizations that are not possible at > > compile time. > > should be on top somewhere, not hidden away inside a giant wall of text > somewhere at the end. Thanks for the suggestion. I'll move it up. Maybe after the first paragraph in Background. Sorry if you received a duplicated message -- I'm resending this in plain text mode. -Rong
