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

In-memory databases require careful tuning and many engineering tricks to achieve good
performance. Such database performance engineering is hard: a plethora of data and …

Domain-specific languages (DSLs) provide high-level and domain-specific abstractions that
allow expressive and concise algorithm descriptions. Since the description in a DSL hides …

High-performance computing applications, such as auto-tuners and domain-specific
languages, rely on generative programming techniques to achieve high performance and …

Current parallel programming frameworks aid developers to a great extent in implementing
applications that exploit parallel hardware resources. Nevertheless, developers require …

Increasingly heterogeneous and hierarchical parallel architectures are now mainstream,
however, most of the traditional programming models are lowlevel and explicit, limiting …

Languages such as OpenCL and CUDA offer a standard interface for general-purpose
programming of GPUs. However, with these languages, programmers must explicitly …

This paper advocates programming high-performance code using partial evaluation. We
present a clean-slate programming system with a simple, annotation-based, online partial …

Data-parallel languages like OpenCL and CUDA are an important means to exploit the
computational power of today's computing devices. In this paper, we deal with two aspects of …

The simplest implementation of a domain-specific language is to embed it in an existing
language using operator overloading. This way, the DSL can inherit parsing, syntax and …