We describe NIMBLE, a system for programming statistical algorithms for general model
structures within R. NIMBLE is designed to meet three challenges: flexible model …

Using existing programming tools, writing high-performance image processing code
requires sacrificing readability, portability, and modularity. We argue that this is a …

Software engineering demands generality and abstraction, performance demands
specialization and concretization. Generative programming can provide both, but the effort …

Graph-based intermediate representations (IRs) are widely used for powerful compiler
optimizations, either interprocedurally in pure functional languages, or intraprocedurally in …

Good software engineering practice demands generalization and abstraction, whereas high
performance demands specialization and concretization. These goals are at odds, and …

Symbolic execution is a powerful program analysis and testing technique. Symbolic
execution engines are usually implemented as interpreters, and the induced interpretation …

The influential pure embedding methodology of embedding domain-specific languages
(DSLs) as libraries into a general-purpose host language forces the DSL designer to commit …

As heterogeneous parallel systems become dominant, application developers are being
forced to turn to an incompatiblemix of low level programming models (eg OpenMP, MPI …

We describe Nikola, a first-order language of array computations embedded in Haskell that
compiles to GPUs via CUDA using a new set of type-directed techniques to support re …

A new language, Feldspar, is presented, enabling high-level and platform-independent
description of digital signal processing (DSP) algorithms. Feldspar is a pure functional …