The problem of probabilistic modeling and inference, at a high-level, can be viewed as constructing a (model, query, inference) tuple, where an inference algorithm implements a query on a model. Notably, the derivatio...
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ISBN:
(纸本)9781450349888
The problem of probabilistic modeling and inference, at a high-level, can be viewed as constructing a (model, query, inference) tuple, where an inference algorithm implements a query on a model. Notably, the derivation of inference algorithms can be a difficult and error-prone task. Hence, researchers have explored how ideas from probabilistic prog ramming can be applied. In the context of constructing these tuples, probabilistic programming can be seen as taking a language-based approach to probabilistic modeling and inference. For instance, by using (1) appropriate languages for expressing models and queries and (2) devising inference techniques that operate on encodings of models (and queries) as program expressions, the task of inference can be automated. In this paper, we describe a compiler that transforms a probabilistic model written in a restricted modeling language and a query for posterior samples given observed data into a Markov Chain Monte Carlo (MCMC) inference algorithm that implements the query. The compiler uses a sequence of intermediate languages (ILs) that guide it in gradually and successively refining a declarative specification of a probabilistic model and the query into an executable MCMC inference algorithm. The compilation strategy produces composable MCMC algorithms for execution on a CPU or GPU.
The proceedings contains 31 papers from the acmsigplan '97 conference on programminglanguagedesign and implementation. Topics discussed include: efficient treatment of language constructs;program compilation;ru...
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The proceedings contains 31 papers from the acmsigplan '97 conference on programminglanguagedesign and implementation. Topics discussed include: efficient treatment of language constructs;program compilation;runtime issues;large-scale optimizations;scheduling;partial evaluation and verification of programs;program analysis;register allocation;parallelism;and mobile computing.
Functional Reactive programming, or FRP. is a general framework for programming hybrid systems in a high-level, declarative manner. The key ideas in FRP are its notions of behaviors and events. Behaviors are time-vary...
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ISBN:
(纸本)9781581131994
Functional Reactive programming, or FRP. is a general framework for programming hybrid systems in a high-level, declarative manner. The key ideas in FRP are its notions of behaviors and events. Behaviors are time-varying, reactive value while events are time-ordered sequences of discrete-time event occurrences. FRP is the essence of Fran, a domain-specific language embedded in Haskell for programming reactive animations, but FRP is now also being used in vision, robotics and other control systems applications. In this paper we explore the formal semantics of FRP and how it relates to an implementation based on streams that represent (and therefore only approximate) continuous behaviors. We show that, in the limit as the sampling interval goes to zero, the implementation is faithful to the formal, continuous semantics, but only when certain constraints on behaviors are observed. We explore the nature of these constraints, which vary amongst the FRP primitives. Our results show both the pou er and limitations of this approach to languagedesign and implementation. As an example of a limitation, we show that streams are incapable of representing instantaneous predicate events over behaviors.
This paper presents the techniques used for the compilation of the data-flow, synchronous language SIGNAL. The key feature of the compiler is that it performs formal calculus on systems of boolean equations. The origi...
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This paper presents a simple, powerful and flexible technique for reasoning about and translating the goal-directed evaluation of programminglanguage constructs that either succeed (and generate sequences of values) ...
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This paper presents a simple, powerful and flexible technique for reasoning about and translating the goal-directed evaluation of programminglanguage constructs that either succeed (and generate sequences of values) or fail. The technique generalizes the Byrd Box, a well-known device for describing Prolog backtracking.
We present lambda PSI, the first probabilistic programminglanguage and system that supports higher-order exact inference for probabilistic programs with first-class functions, nested inference and discrete, continuou...
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ISBN:
(纸本)9781450376136
We present lambda PSI, the first probabilistic programminglanguage and system that supports higher-order exact inference for probabilistic programs with first-class functions, nested inference and discrete, continuous and mixed random variables. lambda PSI's solver is based on symbolic reasoning and computes the exact distribution represented by a program. We show that lambda PSI is practically effective-it automatically computes exact distributions for a number of interesting applications, from rational agents to information theory, many of which could so far only be handled approximately.
High-performance computing applications, such as auto-tuners and domain-specific languages, rely on generative programming techniques to achieve high performance and portability. However, these systems are often imple...
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ISBN:
(纸本)9781450320146
High-performance computing applications, such as auto-tuners and domain-specific languages, rely on generative programming techniques to achieve high performance and portability. However, these systems are often implemented in multiple disparate languages and perform code generation in a separate process from program execution, making certain optimizations difficult to engineer. We leverage a popular scripting language, Lua, to stage the execution of a novel low-level language, Terra. Users can implement optimizations in the high-level language, and use built-in constructs to generate and execute high-performance Terra code. To simplify meta-programming, Lua and Terra share the same lexical environment, but, to ensure performance, Terra code can execute independently of Lua's runtime. We evaluate our design by reimplementing existing multi-language systems entirely in Terra. Our Terra-based auto-tuner for BLAS routines performs within 20% of ATLAS, and our DSL for stencil computations runs 2.3x faster than hand-written C.
Graphical user interfaces (GUIs) mediate many of our interactions with computers. Functional Reactive programming (FRP) is a promising approach to GUI design, providing high-level, declarative, compositional abstracti...
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ISBN:
(纸本)9781450320146
Graphical user interfaces (GUIs) mediate many of our interactions with computers. Functional Reactive programming (FRP) is a promising approach to GUI design, providing high-level, declarative, compositional abstractions to describe user interactions and time-dependent computations. We present Elm, a practical FRP language focused on easy creation of responsive GUIs. Elm has two major features: simple declarative support for Asynchronous FRP;and purely functional graphical layout. Asynchronous FRP allows the programmer to specify when the global ordering of event processing can be violated, and thus enables efficient concurrent execution of FRP programs;long-running computation can be executed asynchronously and not adversely affect the responsiveness of the user interface. Layout in Elm is achieved using a purely functional declarative framework that makes it simple to create and combine text, images, and video into rich multimedia displays. Together, Elm's two major features simplify the complicated task of creating responsive and usable GUIs.
We present an extension of field analysis (see [4]) called related field analysis which is a general technique for proving relationships between two or more fields of an object. We demonstrate the feasibility and appl...
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ISBN:
(纸本)9781581134148
We present an extension of field analysis (see [4]) called related field analysis which is a general technique for proving relationships between two or more fields of an object. We demonstrate the feasibility and applicability of related field analysis by applying it to the problem of removing array bounds checks. For array bounds check removal, we define a pair of related fields to be an integer field and an array field for which the integer field has a known relationship to the length of the array. This related field information can then be used to remove array bounds checks from accesses to the array field. Our results show that related field analysis can remove an average of 50% of the dynamic array bounds checks on-a wide range of applications. We describe the implementation of related field analysis in the Swift optimizing compiler for Java, as well as the optimizations that exploit the results of related field analysis.
We present a new limited form of interprocedural analysis called field analysis that can be used by a compiler to reduce the costs of modern language features such as object-oriented programming, automatic memory mana...
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We present a new limited form of interprocedural analysis called field analysis that can be used by a compiler to reduce the costs of modern language features such as object-oriented programming, automatic memory management, and run-time checks required for type safety. Unlike many previous interprocedural analyses, our analysis is cheap, and does not require access to the entire program. Field analysis exploits the declared access restrictions placed on fields in a modular language (e.g. field access modifiers in Java) in order to determine useful properties of fields of an object, We describe our implementation of field analysis in the Swift optimizing compiler for Java, as well a set of optimizations that exploit the results of field analysis. These optimizations include removal of run-time tests, compile-time resolution of method calls, object inlining, removal of unnecessary synchronization, and stack allocation. Our results demonstrate that field analysis is efficient and effective. Speedups average 7% on a wide range of applications, with some times reduced by up to 27%. Compile time overhead of field analysis is about 10%.
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