604 research outputs found
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
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.
Making an Embedded DBMS JIT-friendly
While database management systems (DBMSs) are highly optimized, interactions
across the boundary between the programming language (PL) and the DBMS are
costly, even for in-process embedded DBMSs. In this paper, we show that
programs that interact with the popular embedded DBMS SQLite can be
significantly optimized - by a factor of 3.4 in our benchmarks - by inlining
across the PL / DBMS boundary. We achieved this speed-up by replacing parts of
SQLite's C interpreter with RPython code and composing the resulting
meta-tracing virtual machine (VM) - called SQPyte - with the PyPy VM. SQPyte
does not compromise stand-alone SQL performance and is 2.2% faster than SQLite
on the widely used TPC-H benchmark suite.Comment: 24 pages, 18 figure
Opportunities for a Truffle-based Golo Interpreter
Golo is a simple dynamically-typed language for the Java Virtual Machine.
Initially implemented as a ahead-of-time compiler to JVM bytecode, it leverages
invokedy-namic and JSR 292 method handles to implement a reasonably efficient
runtime. Truffle is emerging as a framework for building interpreters for JVM
languages with self-specializing AST nodes. Combined with the Graal compiler,
Truffle offers a simple path towards writing efficient interpreters while
keeping the engineering efforts balanced. The Golo project is interested in
experimenting with a Truffle interpreter in the future, as it would provides
interesting comparison elements between invokedynamic versus Truffle for
building a language runtime
Generic Reloading for Languages Based on the Truffle Framework
Programmide käitusaegset uuendamist on põhjalikult uuritud ning selle kasutamine programmeerimiskeelte implementatsioonides kogub hoogu. Senised pakutud lahendused programmide käitusaegse uuendamise osas on rakendatavad ainult konkreetsetele keeltele ja ei ole taaskasutatavad. Käesolevas lõputöös on uuritud seda, kuidas Truffle-nimeline programmeerimiskeelte loomise raamistik suudaks aidata keelte loojatel lisada käitusaegse uuendamise tuge. Autor on loonud taaskasutatava dünaamilise uuendamise lahenduse, mida erinevad Truffle raamistikus loodud keeled saavad kasutada selleks, et vähese vaevaga toetada käitusaegseid uuendusi. Antud lahendusega on võimalik uuendatavaks teha Pythoni, Ruby ja JavasScripti Truffle implementatsioone. Väljatöötatud lahendusel on peaaegu olematu mõju keele tippvõimsusele, kui on sisse lülitatud Truffle täppisajastusega (JIT) kompilaator. See lahendus teeb käitusaegse uuendamise toe lisamise uutele ja tulevastele keeltele märkimisväärselt lihtsamaks.Reloading running programs is a well-researched and increasingly popular feature of programming language implementations. There are plenty of proposed solutions for various existing programming languages, but typically the solutions target a specific language and are not reusable. In this thesis, we explored how the Truffle language implementation framework could aid language creators in adding reloading capabilities to their languages. We created a reusable reloading core that different Truffle-based languages can hook into to support dynamic updates with minimum amount of effort on their part. We demonstrate how the Truffle implementations of Python, Ruby and JavaScript can be made reloadable with the developed solution. With Truffle’s just-in-time compiler enabled, our solution incurs close to zero overhead on steady-state performance. This approach significantly reduces the effort required to add dynamic update support for existing and future languages
Bridging the Gap between Machine and Language using First-Class Building Blocks
High-performance virtual machines (VMs) are increasingly reused for programming languages for which they were not initially designed. Unfortunately, VMs are usually tailored to specific languages, offer only a very limited interface to running applications, and are closed to extensions. As a consequence, extensions required to support new languages often entail the construction of custom VMs, thus impacting reuse, compatibility and performance. Short of building a custom VM, the language designer has to choose between the expressiveness and the performance of the language. In this dissertation we argue that the best way to open the VM is to eliminate it. We present Pinocchio, a natively compiled Smalltalk, in which we identify and reify three basic building blocks for object-oriented languages. First we define a protocol for message passing similar to calling conventions, independent of the actual message lookup mechanism. The lookup is provided by a self-supporting runtime library written in Smalltalk and compiled to native code. Since it unifies the meta- and base-level we obtain a metaobject protocol (MOP). Then we decouple the language-level manipulation of state from the machine-level implementation by extending the structural reflective model of the language with object layouts, layout scopes and slots. Finally we reify behavior using AST nodes and first-class interpreters separate from the low-level language implementation. We describe the implementations of all three first-class building blocks. For each of the blocks we provide a series of examples illustrating how they enable typical extensions to the runtime, and we provide benchmarks validating the practicality of the approaches
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