Camlp4 and Template Haskell

Donham, Jake; Pouillard, Nicolas

doi:10.1145/1900160.1900167

“…. , σ n should still be seen as the top shape, regardless of the labels 6 . The common preferred shape function is extended to find a labelled top shape that best represents the sample.…”

Section: Adding Labelled Top Shapesmentioning

confidence: 98%

“…A number of other advanced type system features could be used to tackle the problem discussed in this paper. The Ur [2] language has a rich system for working with records; metaprogramming [6,19] and multi-stage programming [25] could be used to generate code for the provided types; and gradual typing [20,22] can add typing to existing dynamic languages. As far as we are aware, none of these systems have been used to provide the same level of integration with XML, CSV and JSON.…”

Section: Related and Future Workmentioning

confidence: 99%

Types from data: making structured data first-class citizens in F#

Petříček

¹

,

GuerraGustavo

²

,

SymeDon

³

2016

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Most modern applications interact with external services and access data in structured formats such as XML, JSON and CSV. Static type systems do not understand such formats, often making data access more cumbersome. Should we give up and leave the messy world of external data to dynamic typing and runtime checks? Of course, not! We present F# Data, a library that integrates external structured data into F#. As most real-world data does not come with an explicit schema, we develop a shape inference algorithm that infers a shape from representative sample documents. We then integrate the inferred shape into the F# type system using type providers. We formalize the process and prove a relative type soundness theorem.Our library significantly reduces the amount of data access code and it provides additional safety guarantees when contrasted with the widely used weakly typed techniques.

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“…• There is a bottom shape (6) and any behaves as the top shape, because any shape σ is preferred over any (7).…”

Section: Inferred Shapesmentioning

confidence: 99%

“…A number of other advanced type system features could be used to tackle the problem discussed in this paper. The Ur [2] language has a rich system for working with records; metaprogramming [6,19] and multi-stage programming [25] could be used to generate code for the provided types; and gradual typing [20,22] can add typing to existing dynamic languages. As far as we are aware, none of these systems have been used to provide the same level of integration with XML, CSV and JSON.…”

Section: Related and Future Workmentioning

confidence: 99%

Types from data: making structured data first-class citizens in F#

Petříček

¹

,

Guerra

²

,

Syme

³

2016

Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation

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Most modern applications interact with external services and access data in structured formats such as XML, JSON and CSV. Static type systems do not understand such formats, often making data access more cumbersome. Should we give up and leave the messy world of external data to dynamic typing and runtime checks? Of course, not! We present F# Data, a library that integrates external structured data into F#. As most real-world data does not come with an explicit schema, we develop a shape inference algorithm that infers a shape from representative sample documents. We then integrate the inferred shape into the F# type system using type providers. We formalize the process and prove a relative type soundness theorem.Our library significantly reduces the amount of data access code and it provides additional safety guarantees when contrasted with the widely used weakly typed techniques.

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“…The first takes place at compile-time. It uses a Camlp4 [8] Ocaml syntax extension to type-check the kernel and generate OCaml code. This code embeds the kernel internal representation (KIR) as well as the representation of an external kernel, in order to make Sarek kernels compatible with external ones.…”

Section: Expressing Kernelsmentioning

confidence: 99%

GPGPU Composition with OCaml

Bourgoin

¹

,

Chailloux

²

2014

Proceedings of ACM SIGPLAN International Workshop on Libraries, Languages, and Compilers for Array Programming

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GPGPU programming promises high performance. However, to achieve it, developers must overcome several challenges. The main ones are : write and use hyper-parallel kernels on GPU, manage memory transfers between CPU and GPU, and compose kernels, keeping individual performance of components while optimizing the global performance. In this article, we propose to study the composition by distinguishing the location where it is done : kernel composition on the GPU, kernel generation by the CPU, and overall composition. To achieve it, we use the SPOC library, developed in OCaml. SPOC offers abstractions over the Cuda and OpenCL frameworks. It proposes a specific language, called Sarek, to express kernels and different parallel skeletons to compose them. We show that by increasing the level of abstraction to handle kernels, programs are easier to write and that some optimizations (via kernel generation and transfers scheduling) become possible. Thus, we win on both sides : expressiveness and efficiency.

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Camlp4 and Template Haskell

Cited by 5 publications

References 0 publications

Types from data: making structured data first-class citizens in F#

Types from data: making structured data first-class citizens in F#

Types from data: making structured data first-class citizens in F#

GPGPU Composition with OCaml

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