![]() Unfortunately, the current implementation of (Thin)LTO in LLVM is incompatible with linker scripts for two reasons: Firstly, regular LTO operates by merging all input modules into one and compiling the merged module into a single output file. The linker scripts for complex embedded software projects often contain thousands of such path-based rules to enable features like tightly-coupled memories (TCM), compression, and RAM/ROM assignment. This mapping is expressed using wildcard patterns that are matched to section names and input paths. In particular, they allow the user to describe how sections in the input files should be mapped into the output file. Tobias Edler von Koch, Sergei Larin, Shankar Easwaran and Hemant KulkarniĬustom linker scripts are used pervasively in the embedded world to control the memory layout of the linker's output file. Additionally, we will discuss some of the challenges we face in building a fast GPU compiler that generates performant code. In this talk, we will provide an overview of how we leverage LLVM to implement our GPU compiler: in particular we will provide details about the pipeline we use and we will describe some of the custom passes we added to the LLVM framework that we are considering to contribute to the community. At Apple, we build LLVM-based GPU compilers to serve the embedded GPUs in all our products.The GPU compiler stack is fully LLVM based. The adoption of LLVM to develop GPU compilers has been increasing substantially over the years, thanks to the flexibility of the LLVM framework. Marcello Maggioni and Charu Chandrasekaran Daniel Liew, Cristian Cadar and Alastair Donaldson JIT Fuzzing Solver: A LibFuzzer based constraint solver Project Sulong - Executing LLVM IR on top of a JVM Improving debug information in LLVM to recover optimized-out function parametersĪdding Debug Information and Merge Attribute to Merge-Functions LLVM passes Polyhedral Optimizations and transparent GPU offloading for Julia by Polly Hosseini, Pouya Fotouhi, Chengmo Yang and Guang R. Leveraging Compiler Optimizations to Reduce Runtime Fault Recovery Overhead Farhana Aleen, Elena Demikhovsky and Hideki Saito Carr, Prabhu Rajasekaran, Stijn Volckaert, Yeoul Na, Michael Franz and Mathias PayerĮxtending LLVM’s masked.gather/scatter Intrinsic to Read/write Contiguous Chunks from/to Arbitrary Locations. Priyam Biswas, Alessandro Di Federico, Scott A. Venerable Variadic Vulnerabilities Vanquished Richard Wei, Vikram Adve and Lane SchwartzĮxploiting and improving LLVM's data flow analysis using superoptimizer Shalini Jain, Kamlesh Kumar, Suresh Purini, Dibyendu Das and Ramakrishna UpadrastaĬompiling cross-toolchains with CMake and runtimes buildĭLVM: A Compiler Framework for Deep Learning DSLs ThreadSanitizer APIs for external librariesĪ better shell command-line autocompletion for clangĪ CMake toolkit for migrating C++ projects to clang’s module system.ĭebugging of optimized code: Extending the lifetime of local variables Introsort based sorting function for libc++Ĭode Size Optimization: Interprocedural Outlining at the IR Level Porting LeakSanitizer: A Beginner's Guide Welcome to the back-end: The LLVM machine representation. Daniel Sanders, Aditya Nandakumar and Justin Bogner Xinmin Tian, Hal Finkel, Tb Schardl, Johannes Doerfert and Vikram AdveīoF - Loop and Accelerator Compilation Using Integer Polyhedra Thoughts and State for Representing Parallelism with Minimal IR Extensions in LLVM Devin Coughlin, Artem Dergachev and Anna Zaks Storing Clang data for IDEs and static analysis Serge Guelton, Adrien Guinet, Juan Manuel Martinez and Pierrick Brunetīuilding Your Product Around LLVM Releases Outlook.Ĭhallenges when building an LLVM bitcode Obfuscator Vectorizing Loops with VPlan – Current State and Next Steps Douglas Gregor, Slava Pestov and John McCall Scale, Robust and Regression-Free Loop Optimizations for Scientific Fortran and Modern C++ XRay in LLVM: Function Call Tracing and Analysisĭominator Trees and incremental updates that transcend time Kostya Serebryany, Vitaly Buka and Matt MorehouseĪdding Index‐While‐Building and Refactoring to Clang Structure-aware fuzzing for Clang and LLVM with libprotobuf-mutator The Type Sanitizer: Free Yourself from -fno-strict-aliasingĮnabling Parallel Computing in Chapel with Clang and LLVM The Further Benefits of Explicit Modularization: Modular Codegen Tobias Edler von Koch, Sergei Larin, Shankar Easwaran and Hemant KulkarniĪdvancing Clangd: Bringing persisted indexing to Clang tooling Marcello Maggioni and Charu Chandrasekaranīringing link-time optimization to the embedded world: (Thin)LTO with Linker Scripts Stephen Hines, Nick Desaulniers and Greg HackmannĪpple LLVM GPU Compiler: Embedded Dragons See below for full listing and abstracts.Ĭompiling Android userspace and Linux kernel with LLVM ![]()
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