Lambda, the ultimate label or a simple optimizing compiler for Scheme

Clinger, William D.; Hansen, Lars T.

doi:10.1145/182590.156786

Cited by 14 publications

(16 citation statements)

References 15 publications

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“…Rabbit, by Steele (1978), following on the initial design of the language, demonstrated the possibilities of continuationpassing style and of fast first-class functions. Subsequent systems such as Gambit (Feeley 2014), Bigloo (Serrano and Weis 1995), Larceny (Clinger and Hansen 1994), Stalin (Siskind 1999), and Chez (Dybvig 2011) have pioneered a variety of techniques for static analysis, optimization, and memory management, among others. Most other Scheme implementations are AST or bytecode interpreters.…”

Section: Related Workmentioning

confidence: 99%

Pycket: a tracing JIT for a functional language

Bauman

Bolz

Hirschfeld³

et al. 2015

SIGPLAN Not.

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We present Pycket, a high-performance tracing JIT compiler for Racket. Pycket supports a wide variety of the sophisticated features in Racket such as contracts, continuations, classes, structures, dynamic binding, and more. On average, over a standard suite of benchmarks, Pycket outperforms existing compilers, both Racket's JIT and other highly-optimizing Scheme compilers. Further, Pycket provides much better performance for proxies than existing systems, dramatically reducing the overhead of contracts and gradual typing. We validate this claim with performance evaluation on multiple existing benchmark suites.The Pycket implementation is of independent interest as an application of the RPython meta-tracing framework (originally created for PyPy), which automatically generates tracing JIT compilers from interpreters. Prior work on meta-tracing focuses on bytecode interpreters, whereas Pycket is a high-level interpreter based on the CEK abstract machine and operates directly on abstract syntax trees. Pycket supports proper tail calls and first-class continuations. In the setting of a functional language, where recursion and higher-order functions are more prevalent than explicit loops, the most significant performance challenge for a tracing JIT is identifying which control flows constitute a loop-we discuss two strategies for identifying loops and measure their impact.

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Section: Related Workmentioning

confidence: 99%

Pycket: a tracing JIT for a functional language

Bauman

Bolz

Hirschfeld³

et al. 2015

SIGPLAN Not.

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show abstract

“…For example, partial evaluators such as Schism, Similix, and Pell-Mell lambda-lift source programs and generate scope-free recursive equations [9,11,28]. Compilers such as Larceny and Moby use local, incremental versions of lambda-lifting in their optimizations [10,33], and so did an experimental version of the Glasgow Haskell Compiler [35]. Hanus's compiler for the functional logic language Curry also uses lambda-lifting (personal communication to the first author, FLOPS'02).…”

Section: Lambda-lifting: Whatmentioning

confidence: 99%

“…Today we observe that in the compiler world (Haskell, ML, Scheme), closure conversion has prevailed, with only one exception in Scheme [10]. Conversely, in the program-transformation world [9,11,28], lambda-lifting has prevailed.…”

Section: Closure Conversionmentioning

confidence: 99%

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Lambda-Lifting in Quadratic Time

Danvy¹,

Schultz²

2003

BRICS

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Lambda-lifting is a program transformation used in compilers and in partial evaluators and that operates in cubic time. In this article, we show how to reduce this complexity to quadratic time, and we present a flow-sensitive lambda-lifter that also works in quadratic time.Lambda-lifting transforms a block-structured program into a set of recursive equations, one for each local function in the source program. Each equation carries extra parameters to account for the free variables of the corresponding local function and of all its callees. It is the search for these extra parameters that yields the cubic factor in the traditional formulation of lambda-lifting, which is due to Johnsson. This search is carried out by a transitive closure.Instead, we partition the call graph of the source program into strongly connected components, based on the simple observation that all functions in each component need the same extra parameters and thus a transitive closure is not needed. We therefore simplify the search for extra parameters by treating each strongly connected component instead of each function as a unit, thereby reducing the time complexity of lambda-lifting from O(n 3 log n) to O(n 2 log n), where n is the size of the program. Since a lambda-lifter can output programs of size O(n 2 ), we believe that our algorithm is close to optimal. * A preliminary version of this article was presented at FLOPS'02 [16].

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“…In their Scheme compiler Twobit, Clinger and Hansen also use lambdalifting [10]. They, however, modify the flow equations to reduce the arity of lambda-lifted procedures.…”

Section: Curried and Lazy Vs Uncurried And Eager Programsmentioning

confidence: 99%

Lambda-Dropping: Transforming Recursive Equations into Programs with Block Structure

Danvy¹,

Schultz²

1999

BRICS

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Lambda-lifting a block-structured program transforms it into a set of recursive equations. We present the symmetric transformation: lambdadropping. Lambda-dropping a set of recursive equations restores block structure and lexical scope.For lack of block structure and lexical scope, recursive equations must carry around all the parameters that any of their callees might possibly need. Both lambda-lifting and lambda-dropping thus require one to compute Def/Use paths:• for lambda-lifting: each of the functions occurring in the path of a free variable is passed this variable as a parameter;• for lambda-dropping: parameters which are used in the same scope as their definition do not need to be passed along in their path.A program whose blocks have no free variables is scope-insensitive. Its blocks are then free to float (for lambda-lifting) or to sink (for lambdadropping) along the vertices of the scope tree. *

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Lambda, the ultimate label or a simple optimizing compiler for Scheme

Cited by 14 publications

References 15 publications

Pycket: a tracing JIT for a functional language

Pycket: a tracing JIT for a functional language

Lambda-Lifting in Quadratic Time

Lambda-Dropping: Transforming Recursive Equations into Programs with Block Structure

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