Stories with Tag LLVM

• A Clang regression related to switch statements and inlining

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  Posted: 2025-02-18 12:38:08

  Verbose tl;dr

  A recent Clang optimization introduced in version 17 regressed performance when compiling code containing large switch statements within inlined functions. This regression manifested as significantly increased compile times, sometimes by orders of magnitude, and occasionally resulted in internal compiler errors. The issue stems from Clang's attempt to optimize switch lowering by transforming it into a series of conditional moves based on jump tables. This optimization, while beneficial in some cases, interacts poorly with inlining, exploding the complexity of the generated intermediate representation (IR) when a function with a large switch is inlined multiple times. This ultimately overwhelms the compiler's later optimization passes. A workaround involves disabling the problematic optimization via a compiler flag (-mllvm -switch-to-lookup-table-threshold=0) until a proper fix is implemented in a future Clang release.

  This blog post details a performance regression discovered by the author, Adrian Nicula, in Clang versions 15 and 16 concerning the compilation of C++ code containing large switch statements within inline functions. The issue arises specifically when these switch statements are located inside inline functions that are called repeatedly within a hot loop. Prior to Clang 15, the compiler effectively optimized these scenarios, resulting in efficient code execution. However, in Clang 15 and 16, the optimization strategy changed, leading to a significant performance degradation in specific circumstances.

  The core problem stems from how Clang handles jump tables, a common optimization technique for switch statements. Previously, when an inline function with a large switch was called repeatedly, Clang would generate a single jump table for the switch statement and reuse it across all call sites. This approach minimized code size and maximized performance.

  Beginning with Clang 15, the compiler seemingly changed its inlining heuristics. Instead of creating a single shared jump table, Clang now generates a separate jump table for each instance of the inlined function within the loop. This duplication significantly increases the code size, particularly for large switch statements with numerous cases. The larger code size negatively impacts instruction cache performance, leading to the observed performance regression.

  Nicula demonstrates the issue with a concise example involving a benchmarking program that measures the execution time of code containing a large switch statement within an inline function. He provides performance measurements across different Clang versions, clearly showing the performance drop in versions 15 and 16. The benchmark also highlights that the issue only manifests when the inline function is called a substantial number of times within a loop.

  The author further investigates the generated assembly code, confirming the proliferation of jump tables in Clang 15 and 16 compared to earlier versions. This analysis solidifies the hypothesis that the change in jump table generation is the root cause of the performance problem.

  While Nicula did not pinpoint the exact commit introducing this regression, he suspects it may be related to modifications in Clang's inlining or jump table generation logic around the time of Clang 15's release. The author concludes by recommending users experiencing similar performance issues to revert to Clang 14 or explore compiler flags related to inlining and optimization to potentially mitigate the problem. He also expresses hope that the Clang community will address this regression in future releases.

  • Clang
  • compiler
  • C++
  • C
  • Regression
  • Switch Statement
  • Inlining
  • optimization
  • Code Generation
  • LLVM
  • bug
  • performance

  Summary of Comments ( 2 )
  https://news.ycombinator.com/item?id=43088797

  Verbose tl;dr

  The Hacker News comments discuss a performance regression in Clang involving large switch statements and inlining. Several commenters confirm experiencing similar issues, particularly when compiling large codebases. Some suggest the regression might be related to changes in the inlining heuristics or the way Clang handles jump tables. One commenter points out that using a constexpr hash table for large switches can be a faster alternative. Another suggests profiling and selective inlining as a workaround. The lack of clear identification of the root cause and the potential impact on compile times and performance are highlighted as concerning. Some users express frustration with the frequency of such regressions in Clang.

  The Hacker News post discussing the Clang regression related to switch statements and inlining sparked a conversation revolving primarily around compiler optimization, code generation, and debugging challenges. Several commenters delved into the technical intricacies of the issue.

  One commenter highlighted the complexities involved in compiler optimization, specifically mentioning the difficulty in striking a balance between performance gains and potential code bloat. They pointed out that aggressive inlining, while often beneficial, can sometimes lead to larger binaries and potentially slower execution in certain scenarios, as was seemingly the case with the Clang regression described in the article. This commenter also touched upon the trade-offs compilers must make and how these decisions can sometimes have unforeseen consequences.

  Another commenter focused on the debugging challenges introduced by such optimizations. They argued that overly aggressive inlining can obscure the relationship between the original source code and the generated assembly, making it harder to debug issues. This difficulty stems from the fact that the inlined code is effectively "merged" into the calling function, making it harder to trace back to the original source location when stepping through a debugger.

  The discussion also touched upon the specifics of switch statement optimization. One commenter explained how compilers often transform switch statements into various forms, such as jump tables or binary search trees, depending on the density and distribution of the cases. They suggested that the Clang regression might be related to a suboptimal choice of switch implementation in specific scenarios.

  Furthermore, a commenter mentioned the importance of profiling and benchmarking in identifying and addressing such performance regressions. They emphasized that relying solely on theoretical analysis of code transformations can be misleading and that empirical data is crucial for understanding the actual impact of compiler optimizations.

  Finally, some commenters discussed potential workarounds and suggested exploring compiler flags to fine-tune inlining behavior or to disable specific optimizations. This highlighted the importance of having granular control over the compiler's optimization strategies to mitigate potential performance issues.

  Overall, the comments on Hacker News provided valuable insights into the technical nuances of the Clang regression, focusing on the challenges related to compiler optimization, debugging, and the importance of profiling and benchmarking. The discussion demonstrated a deep understanding of compiler internals and offered practical suggestions for dealing with similar issues.

• Ways to generate SSA

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  Posted: 2025-02-11 07:21:21

  Verbose tl;dr

  The blog post explores various methods for generating Static Single Assignment (SSA) form, a crucial intermediate representation in compilers. It starts with the basic concepts of SSA, explaining dominance and phi functions. Then, it delves into different algorithms for SSA construction, including the classic dominance frontier algorithm and the more modern Cytron et al. algorithm. The post emphasizes the performance implications of these algorithms, highlighting how Cytron's approach optimizes placement of phi functions. It also touches upon less common methods like the iterative and memory-efficient Chaitin-Briggs algorithm. Finally, it briefly discusses register allocation and how SSA simplifies this process by providing a clear data flow representation.

  This blog post, titled "Ways to generate SSA," delves into the intricacies of Static Single Assignment (SSA) form, a crucial intermediate representation (IR) used in compilers for optimization. The author begins by establishing the importance of SSA, emphasizing its role in simplifying and enhancing the effectiveness of various compiler optimizations. SSA form, they explain, achieves this by ensuring that each variable is assigned a value only once, thereby simplifying data flow analysis and enabling more powerful optimization techniques.

  The post then proceeds to meticulously dissect several prominent methods for converting conventional code into SSA form. The first approach explored is the dominance frontier algorithm. This algorithm systematically identifies points in the code where different definitions of a variable might "merge," requiring the introduction of phi functions to reconcile these potentially conflicting values and maintain the single-assignment property. The author provides a detailed explanation of the dominance frontier concept, illustrating how it helps pinpoint the precise locations for phi function insertion.

  Following the dominance frontier method, the post then examines an alternative approach based on the use of an explicit stack. This method, the author explains, offers a conceptually simpler way to manage variable assignments during the SSA conversion process. By employing a stack to track the current version of each variable, the compiler can readily determine the appropriate version to use at any given point in the code, again ensuring the single-assignment property is upheld.

  The author then compares and contrasts these two methods, highlighting the trade-offs between the dominance frontier algorithm's potential for greater efficiency and the stack-based approach's relative simplicity. The discussion considers the computational complexity of each method and the potential impact on subsequent optimization passes.

  Finally, the blog post concludes by briefly touching upon the concept of minimal SSA form. This variation of SSA, the author explains, aims to minimize the number of inserted phi functions, further enhancing the efficiency of subsequent compiler optimizations. The post suggests that minimal SSA form, while beneficial, can be more computationally expensive to generate. Overall, the post provides a comprehensive overview of the core techniques involved in generating SSA form, offering valuable insights into their respective strengths and weaknesses.

  • SSA
  • Static Single Assignment
  • compiler optimization
  • Intermediate Representation
  • Code Analysis
  • program analysis
  • Data Flow Analysis
  • Control Flow Graph
  • LLVM
  • compiler design
  • Code Generation

  Summary of Comments ( 31 )
  https://news.ycombinator.com/item?id=43009952

  Verbose tl;dr

  HN users generally agreed with the author's premise that Single Static Assignment (SSA) form is beneficial for compiler optimization. Several commenters delved into the nuances of different SSA construction algorithms, highlighting Cytron et al.'s algorithm for its efficiency and prevalence. The discussion also touched on related concepts like minimal SSA, pruned SSA, and the challenges of handling irreducible control flow graphs. Some users pointed out practical considerations like register allocation and the trade-offs between SSA forms. One commenter questioned the necessity of SSA for modern optimization techniques, sparking a brief debate about its relevance. Others offered additional resources, including links to relevant papers and implementations.

  The Hacker News post titled "Ways to generate SSA" (https://news.ycombinator.com/item?id=43009952) discusses various methods for generating Static Single Assignment (SSA) form, as described in the linked blog post. The comments section contains several insightful contributions, focusing primarily on the practicalities and nuances of SSA implementation.

  One commenter points out that the blog post uses an unconventional definition of dominance, focusing on dominance frontiers rather than the typical understanding of dominance relations in compiler design. This commenter suggests that the approach described in the blog post isn't technically generating SSA in the traditional sense, but rather a variant that directly calculates liveness information. This sparked a brief discussion about the different perspectives on dominance and how they relate to SSA construction.

  Another significant thread discusses the performance implications of different SSA construction algorithms. One commenter highlights the Cytron et al. algorithm as a particularly efficient approach. This led to a further discussion about the trade-offs between different algorithms, with some commenters arguing that simpler algorithms can be more practical in certain scenarios, despite potentially being less theoretically optimal. Specific mention is made of the impact on register allocation and the complexities introduced by handling exceptions and other control flow irregularities.

  Furthermore, the discussion touches upon the challenges of implementing SSA in real-world compilers. One commenter shares their personal experience working on the V8 JavaScript engine, noting that the performance benefits of SSA can be substantial, but that the actual implementation can be quite complex due to the need to handle JavaScript's dynamic nature and features like eval. Another commenter mentions the prevalence of SSA in modern optimizing compilers, reinforcing its importance in achieving high performance.

  Finally, some comments provide additional context and resources related to SSA. One commenter links to a relevant Wikipedia article, while another recommends a specific chapter in the "Engineering a Compiler" textbook for further reading. These comments serve to broaden the discussion and provide valuable learning resources for those interested in delving deeper into the topic of SSA.

• Apple is open sourcing Swift Build

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  Posted: 2025-02-01 16:44:53

  Verbose tl;dr

  Apple is open-sourcing Swift Build, the build system used to create Swift itself and related projects. This move aims to improve build performance, enable more seamless integration with other build systems, and foster community involvement in its evolution. The open-sourcing effort will happen gradually, focusing initially on the build system's core components, including the build planning framework and the driver responsible for invoking build tools. Future plans include exploring alternative build executors and potentially supporting other languages beyond Swift. This change is expected to increase transparency, encourage broader adoption, and facilitate the development of new tools and integrations by the community.

  The Swift community has announced a significant advancement in the evolution of its build system: the open sourcing of Swift Build. This marks a pivotal moment, transitioning the system from a closed-source component tightly coupled with the Swift compiler to a standalone, community-driven project. The blog post meticulously outlines the motivations and benefits of this transition, as well as the technical details of the new architecture.

  Historically, the build system responsible for compiling Swift projects was integrated directly into the Swift compiler. While this approach offered certain advantages in the early stages of Swift's development, it presented increasing challenges as the language and its ecosystem matured. The monolithic nature of the compiler-integrated build system made it difficult to iterate rapidly on build features independently of the compiler itself. Furthermore, it hampered the ability of external developers and tool authors to contribute to the build system's evolution or adapt it to their specific needs.

  The newly open-sourced Swift Build addresses these limitations by introducing a modular and extensible architecture. It is designed to be language-agnostic, capable of building projects written in C, C++, Objective-C, and of course, Swift. This broader applicability opens up possibilities for cross-language projects and integration with other build systems. The system leverages the Swift Package Manager's package model for defining project structure and dependencies, providing a familiar and consistent experience for Swift developers.

  One of the key innovations within Swift Build is the adoption of the Build System Interface (BSI), which serves as a well-defined communication layer between the build system and the underlying build tools. This abstraction allows for greater flexibility and choice in the tools used for the actual compilation and linking processes. Developers can, for instance, swap out different compilers or linkers based on their specific requirements, without needing to modify the core build system logic. The BSI further promotes innovation by enabling the creation of entirely new build tools that can integrate seamlessly with Swift Build.

  The open-sourcing of Swift Build also facilitates community involvement. By making the source code publicly available, the Swift team invites contributions from developers worldwide, fostering a collaborative environment for enhancing the build system's capabilities and addressing any shortcomings. This collaborative approach is expected to accelerate the development and maturation of Swift Build, leading to a more robust and feature-rich build experience for all Swift developers. Furthermore, the move towards open source fosters transparency and trust within the community, allowing developers to scrutinize and understand the inner workings of the build system.

  The blog post emphasizes that this transition is a gradual process. Initially, Swift Build will be focused on supporting Swift Package Manager projects on macOS, with future plans to extend support to other platforms and integrate with existing Xcode projects. The Swift team encourages community feedback and participation in shaping the future of Swift Build, emphasizing its importance in the continued growth and success of the Swift ecosystem.

  • Swift
  • Swift Build
  • build system
  • Open Source
  • Apple
  • compiler
  • programming language
  • Software Development
  • developer tools
  • LLVM

  Summary of Comments ( 50 )
  https://news.ycombinator.com/item?id=42899703

  Verbose tl;dr

  HN commenters generally expressed cautious optimism about Apple open sourcing Swift Build. Some praised the potential for improved build times and cross-platform compatibility, particularly for non-Apple platforms. Several brought up concerns about how actively Apple will maintain the open-source project and whether it will truly benefit the wider community or primarily serve Apple's internal needs. Others questioned the long-term implications, wondering if this move signals Apple's eventual shift away from Xcode. A few commenters also discussed the technical details, comparing Swift Build to other build systems like Bazel and CMake, and speculating about potential integration challenges. Some highlighted the importance of community involvement for the project's success.

  The Hacker News post "Apple is open sourcing Swift Build" generated a fair number of comments discussing the announcement of Swift Build's open-sourcing. Several commenters expressed cautious optimism, acknowledging that this move could potentially improve Swift's ecosystem, especially for server-side development and cross-platform compatibility. They also hoped for better integration with other build systems and improved build times.

  Some commenters delved into more technical aspects, discussing the potential benefits of using Bazel, the build system underlying Swift Build. They pointed to its potential for remote caching and distributed builds, leading to faster build times, particularly for large projects. The potential for integrating with existing Bazel rules and extensions was also mentioned as a plus.

  A few comments expressed skepticism, questioning whether this open-sourcing would truly be beneficial to the community. One commenter pointed out the challenge of making Bazel accessible to developers unfamiliar with its complexities. Another commenter questioned the level of community involvement Apple would allow and speculated on whether this move was primarily motivated by Apple's internal needs.

  The potential impact on other build systems like CMake and Swift Package Manager (SPM) was also a topic of discussion. Some users wondered if this signaled the eventual deprecation of SPM. Others speculated that Swift Build might coexist with or even enhance these existing systems.

  Several users highlighted the current limitations of Swift's build tooling, especially around dependency management and build times. They expressed hope that open-sourcing Swift Build would address these issues, leading to a smoother development experience.

  A couple of comments also touched upon the licensing aspect of the open-sourcing, emphasizing the importance of a permissive license for wider community adoption and contribution. One user pointed out the Apache 2.0 license would enable its use in commercial products without requiring source code disclosure.

  Finally, there were a few comments expressing general excitement about the announcement, seeing it as a positive step for the Swift community and a potential catalyst for further growth and innovation.

• Tilde, My LLVM Alternative

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  Posted: 2025-01-21 17:33:52

  Verbose tl;dr

  Yasser is developing "Tilde," a new compiler infrastructure designed as a simpler, more modular alternative to LLVM. Frustrated with LLVM's complexity and monolithic nature, he's building Tilde with a focus on ease of use, extensibility, and better diagnostics. The project is in its early stages, currently capable of compiling a subset of C and targeting x86-64 Linux. Key differentiating features include a novel intermediate representation (IR) designed for efficient analysis and transformation, a pipeline architecture that facilitates experimentation and customization, and a commitment to clear documentation and a welcoming community. While performance isn't the primary focus initially, the long-term goal is to be competitive with LLVM.

  Yasser, the author, introduces "Tilde," their personal project aimed at creating a from-scratch alternative to the LLVM compiler infrastructure. Driven by a desire to learn more about compilers and explore different design decisions, they embarked on this ambitious undertaking. Tilde isn't intended to replace or compete with LLVM, but rather serves as an educational exercise and a platform for experimentation.

  The post details the current state of Tilde, which is still in its early stages. It currently supports a minimal subset of the C language, focusing on basic integer arithmetic, function calls, global and local variables, and control flow constructs like if statements and for loops. The author explicitly mentions the omission of more complex features like structures, floating-point numbers, and pointers, emphasizing the project's nascent nature.

  The compilation process in Tilde is outlined, starting with parsing the input C code into an Abstract Syntax Tree (AST). This AST is then transformed into a simpler, three-address code intermediate representation (IR). From this IR, Tilde generates assembly code for the x86-64 architecture. The author details the register allocation strategy, which currently uses a simple, non-optimized approach. Specifically, Tilde assigns a new register for every variable, leading to suboptimal code generation but simplifying the implementation. Future optimizations are planned, but not yet implemented.

  The author emphasizes their choice of Zig as the implementation language for Tilde, highlighting Zig's self-hosting capabilities and control over memory management as key factors. This allows for easier debugging and a more streamlined development process compared to using C or C++.

  The post concludes with a discussion of future plans for Tilde. These include expanding the supported C features, implementing better register allocation, incorporating optimizations like constant folding and dead code elimination, and exploring alternative backend targets beyond x86-64. The author expresses excitement about the project's potential and invites feedback from the community. The overall tone suggests a passion for compiler design and a commitment to the ongoing development of Tilde, albeit as a personal learning endeavor rather than a production-ready tool.

  • LLVM
  • compiler
  • Programming Languages
  • Alternative Compiler
  • Compiler Infrastructure
  • Tilde
  • Open Source
  • developer tools
  • Code Generation
  • optimization
  • IR
  • Intermediate Representation

  Summary of Comments ( 41 )
  https://news.ycombinator.com/item?id=42782872

  Verbose tl;dr

  Hacker News users discuss the author's approach to building a compiler, "Tilde," positioned as an LLVM alternative. Several commenters express skepticism about the project's practicality and scope, questioning the rationale behind reinventing LLVM, especially given its maturity and extensive community. Some doubt the performance claims and suggest benchmarks are needed. Others appreciate the author's ambition and the technical details shared, seeing value in exploring alternative compiler designs even if Tilde doesn't replace LLVM. A few users offer constructive feedback on specific aspects of the compiler's architecture and potential improvements. The overall sentiment leans towards cautious interest with a dose of pragmatism regarding the challenges of competing with an established project like LLVM.

  The Hacker News thread for "Tilde, My LLVM Alternative" contains a moderate number of comments, many of which delve into technical details and offer informed perspectives on the project. While there's enthusiasm for the ambition and potential of a simpler compiler backend, there's also a healthy dose of skepticism and pragmatic analysis of the challenges involved.

  Several commenters acknowledge the complexity of LLVM and the potential benefits of a simpler, more approachable alternative, particularly for educational purposes or niche use cases. Some express interest in following the project's development and appreciate the author's willingness to tackle such a complex undertaking.

  However, many comments also highlight the significant hurdles faced by such a project. The sheer size and maturity of LLVM, coupled with its extensive community and tooling, are seen as major advantages that Tilde would struggle to replicate. Some commenters question whether the performance gains touted by the author are realistically achievable or sustainable in the long run. Concerns are raised about the potential for fragmentation within the compiler ecosystem and the difficulty of attracting a sufficient developer community to support and maintain a new backend.

  A few compelling comments include:

  • Discussions around niche use cases: Some commenters suggest that Tilde could find a place in specialized domains like embedded systems or specific hardware architectures where LLVM's overhead might be less desirable. This prompts further discussion about the trade-offs between generality and performance optimization.
  • Debate about performance claims: The author's claims regarding performance improvements are met with some skepticism. Commenters point out the importance of rigorous benchmarking and the need to consider various factors beyond raw compilation speed. The discussion revolves around the specific optimizations implemented in Tilde and how they compare to LLVM's existing optimization strategies.
  • Exploration of alternative approaches: Several commenters suggest alternative approaches to achieving similar goals, such as focusing on improving LLVM's documentation and tooling or developing a simplified frontend that abstracts away some of LLVM's complexity. This sparks a conversation about the best way to address the perceived learning curve associated with LLVM.
  • Emphasis on community building: The importance of community involvement is repeatedly emphasized. Commenters suggest that the project's success hinges on attracting contributors and building a vibrant ecosystem around Tilde. This leads to a discussion about the challenges of attracting developers to a new project, particularly in a field already dominated by a well-established player like LLVM.

  Overall, the comments reflect a cautious but intrigued response to the "Tilde" project. While acknowledging the author's ambition and the potential value of a simplified compiler backend, the discussion reveals a strong awareness of the significant challenges involved and the importance of carefully considering the project's goals and scope.