Open Programming Language Interpreters

Context: This paper presents the concept of open programming language interpreters and the implementation of a framework-level metaobject protocol (MOP) to support them. Inquiry: We address the problem of dynamic interpreter adaptation to tailor the interpreter's behavior on the task to be solved and to introduce new features to fulfill unforeseen requirements. Many languages provide a MOP that to some degree supports reflection. However, MOPs are typically language-specific, their reflective functionality is often restricted, and the adaptation and application logic are often mixed which hardens the understanding and maintenance of the source code. Our system overcomes these limitations. Approach: We designed and implemented a system to support open programming language interpreters. The prototype implementation is integrated in the Neverlang framework. The system exposes the structure, behavior and the runtime state of any Neverlang-based interpreter with the ability to modify it. Knowledge: Our system provides a complete control over interpreter's structure, behavior and its runtime state. The approach is applicable to every Neverlang-based interpreter. Adaptation code can potentially be reused across different language implementations. Grounding: Having a prototype implementation we focused on feasibility evaluation. The paper shows that our approach well addresses problems commonly found in the research literature. We have a demonstrative video and examples that illustrate our approach on dynamic software adaptation, aspect-oriented programming, debugging and context-aware interpreters. Importance: To our knowledge, our paper presents the first reflective approach targeting a general framework for language development. Our system provides full reflective support for free to any Neverlang-based interpreter. We are not aware of any prior application of open implementations to programming language interpreters in the sense defined in this paper. Rather than substituting other approaches, we believe our system can be used as a complementary technique in situations where other approaches present serious limitations

Simple and Effective Type Check Removal through Lazy Basic Block Versioning

Dynamically typed programming languages such as JavaScript and Python defer type checking to run time. In order to maximize performance, dynamic language VM implementations must attempt to eliminate redundant dynamic type checks. However, type inference analyses are often costly and involve tradeoffs between compilation time and resulting precision. This has lead to the creation of increasingly complex multi-tiered VM architectures. This paper introduces lazy basic block versioning, a simple JIT compilation technique which effectively removes redundant type checks from critical code paths. This novel approach lazily generates type-specialized versions of basic blocks on-the-fly while propagating context-dependent type information. This does not require the use of costly program analyses, is not restricted by the precision limitations of traditional type analyses and avoids the implementation complexity of speculative optimization techniques. We have implemented intraprocedural lazy basic block versioning in a JavaScript JIT compiler. This approach is compared with a classical flow-based type analysis. Lazy basic block versioning performs as well or better on all benchmarks. On average, 71% of type tests are eliminated, yielding speedups of up to 50%. We also show that our implementation generates more efficient machine code than TraceMonkey, a tracing JIT compiler for JavaScript, on several benchmarks. The combination of implementation simplicity, low algorithmic complexity and good run time performance makes basic block versioning attractive for baseline JIT compilers

Interprocedural Type Specialization of JavaScript Programs Without Type Analysis

Dynamically typed programming languages such as Python and JavaScript defer type checking to run time. VM implementations can improve performance by eliminating redundant dynamic type checks. However, type inference analyses are often costly and involve tradeoffs between compilation time and resulting precision. This has lead to the creation of increasingly complex multi-tiered VM architectures. Lazy basic block versioning is a simple JIT compilation technique which effectively removes redundant type checks from critical code paths. This novel approach lazily generates type-specialized versions of basic blocks on-the-fly while propagating context-dependent type information. This approach does not require the use of costly program analyses, is not restricted by the precision limitations of traditional type analyses. This paper extends lazy basic block versioning to propagate type information interprocedurally, across function call boundaries. Our implementation in a JavaScript JIT compiler shows that across 26 benchmarks, interprocedural basic block versioning eliminates more type tag tests on average than what is achievable with static type analysis without resorting to code transformations. On average, 94.3% of type tag tests are eliminated, yielding speedups of up to 56%. We also show that our implementation is able to outperform Truffle/JS on several benchmarks, both in terms of execution time and compilation time.Comment: 10 pages, 10 figures, submitted to CGO 201

Collapsing towers of interpreters

Given a tower of interpreters, i.e., a sequence of multiple interpreters interpreting one another as input programs, we aim to collapse this tower into a compiler that removes all interpretive overhead and runs in a single pass. In the real world, a use case might be Python code executed by an x86 runtime, on a CPU emulated in a JavaScript VM, running on an ARM CPU. Collapsing such a tower can not only exponentially improve runtime performance, but also enable the use of base-language tools for interpreted programs, e.g., for analysis and verification. In this paper, we lay the foundations in an idealized but realistic setting. We present a multi-level lambda calculus that features staging constructs and stage polymorphism: based on runtime parameters, an evaluator either executes source code (thereby acting as an interpreter) or generates code (thereby acting as a compiler). We identify stage polymorphism, a programming model from the domain of high-performance program generators, as the key mechanism to make such interpreters compose in a collapsible way. We present Pink, a meta-circular Lisp-like evaluator on top of this calculus, and demonstrate that we can collapse arbitrarily many levels of self-interpretation, including levels with semantic modifications. We discuss several examples: compiling regular expressions through an interpreter to base code, building program transformers from modi ed interpreters, and others. We develop these ideas further to include reflection and reification, culminating in Purple, a reflective language inspired by Brown, Blond, and Black, which realizes a conceptually infinite tower, where every aspect of the semantics can change dynamically. Addressing an open challenge, we show how user programs can be compiled and recompiled under user-modified semantics.Parts of this research were supported by ERC grant 321217, NSF awards 1553471 and 1564207, and DOE award DE-SC0018050

Speculative Staging for Interpreter Optimization

Interpreters have a bad reputation for having lower performance than just-in-time compilers. We present a new way of building high performance interpreters that is particularly effective for executing dynamically typed programming languages. The key idea is to combine speculative staging of optimized interpreter instructions with a novel technique of incrementally and iteratively concerting them at run-time. This paper introduces the concepts behind deriving optimized instructions from existing interpreter instructions---incrementally peeling off layers of complexity. When compiling the interpreter, these optimized derivatives will be compiled along with the original interpreter instructions. Therefore, our technique is portable by construction since it leverages the existing compiler's backend. At run-time we use instruction substitution from the interpreter's original and expensive instructions to optimized instruction derivatives to speed up execution. Our technique unites high performance with the simplicity and portability of interpreters---we report that our optimization makes the CPython interpreter up to more than four times faster, where our interpreter closes the gap between and sometimes even outperforms PyPy's just-in-time compiler.Comment: 16 pages, 4 figures, 3 tables. Uses CPython 3.2.3 and PyPy 1.

A Tracing JIT Compiler for Erlang using LLVM

We have modified the Erlang runtime to add support for a tracing just-in-time (JIT) compiler, similar to Mozilla’s TraceMonkey. Tracing is a technique to augment an existing interpreter with a JIT simply by recording the instructions executed during a loop iteration, and then generate optimized native code from this. Tracing compilers are particularly suited to optimize number crunching tight loops, an area where Erlang traditionally has been lacking. We make use of the LLVM compiler library to optimize and emit native code. In micro benchmarks we show some major improvements, reducing execution time by up to 75%. However, from an engineering point of view, we conclude that the effort of an industrial strength implementation would be substantial – essentially reimplementing large parts of Erlang’s interpreter – and discuss a potential solution based on recent research in the area.Nästan alla moderna programspråk använder en interpretator – en flexibel och praktisk om än långsam lösning. Vi prövar ett enkelt sätt att kraftigt öka prestandan på Erlangs interpretator