
Explore building a CPU using GPT for every instruction, compiling C code to LLVM-IR. Learn about compilers, virtual machines, and innovative applications of language models in computing.

Explore QDFO, a dataflow-based optimization approach for Microsoft QIR, improving code efficiency and readability through preprocessing and redundancy reduction in quantum computing programs.

Toolset for detecting vulnerabilities in iOS apps: download and decrypt, decompile, statically analyze, and present results. Focuses on high-level semantics reconstruction and common mobile app security flaws.

Explore automatic exploit generation through program analysis techniques, including instrumentation and symbolic execution, with practical demonstrations and tool insights.

Explore LLVM's intermediate representation, its complexities, and the Vellvm project's approach to formal verification using Coq, aimed at ensuring compiler reliability and security.

Explore Rust's compiler architecture to build static analysis tools and compilers. Learn to implement a simple LISP and create JIT-like compilers using Rust's codegen machinery.

Explore next-gen disassembly framework for multi-architecture binary analysis. Learn about Capstone engine's features, design challenges, and potential applications in reversing, exploit development, and malware detection.

Explore hardware-enforced restrictions on computational complexity using JIT compilation and Intel's Processor Tracing to improve security through limited return-oriented programming.

Explore runtime and compile-time optimizations in Java and C++, comparing JIT and AOT compilers for improved performance and efficiency in software development.

Explore LLVM compiler optimizations for undefined behavior, uncovering hidden bugs and security vulnerabilities in C/C++ programs through advanced static analysis techniques.

Discover how LLVM simplifies compiler creation for domain-specific languages, combining C++ performance with unique linguistic features. Learn to build powerful, efficient DSLs.

Explore Julia's Lisp-inspired features and modern optimization techniques for scientific computing, highlighting its high-level syntax and high-performance capabilities.

Explore efforts to build the upstream Linux kernel using Clang, including patches to the build system, kernel code, and LLVM/Clang. Learn how to build a kernel with Clang and discover remaining challenges.

Explore efforts to enable TensorFlow on open-source GPUs using SYCL, LLVM, and OpenCL. Learn about challenges and progress in deploying AI/ML frameworks without proprietary NVIDIA CUDA stack.

Explore LLVM's adoption for Linux kernel builds, 2020 achievements, and future focus. Learn about tradeoffs, upcoming work, and how to contribute to kernel and toolchain development.

Explore WebAssembly's potential to boost web app performance using pre-optimized execution code, LLVM, and languages like C++ or Rust. Learn about DOM access, JavaScript integration, and multithreading in WebAssembly.

Explore LLVM and clang libraries for custom C++ tools. Learn AST representation, static analysis, and source-to-source transformations to enhance workflow and productivity.

Explore x86_64 LLVM Linux project updates, current issues, and strategies for upstreaming work into the Linux Kernel or LLVM/Clang, with a focus on resolving challenges and accelerating progress.

Exploring LLVM adoption for Hexagon DSP, covering Linux kernel and user space compilation challenges, solutions, and ongoing issues in replacing GCC with LLVM toolchain.

Explore Clang and LLVM for Linux kernel development, covering priorities, tools, and techniques to enhance compilation, debugging, and code analysis processes.

Learn how to leverage GCC's regression test suite to enhance LLVM's testing capabilities, improving compiler reliability and performance.