We consider multiphysics applications from algorithmic and architectural perspectives,
where “algorithmic” includes both mathematical analysis and computational complexity, and …

Despite the increasing importance of in silico experiments to the scientific discovery process,
state-of-the-art software engineering practices are rarely adopted in computational science …

3D visual computing data are often spatially sparse. To exploit such sparsity, people have
developed hierarchical sparse data structures, such as multi-level sparse voxel grids …

The performance bottlenecks of graph applications depend not only on the algorithm and
the underlying hardware, but also on the size and structure of the input graph. As a result …

This paper presents the design and implementation of PolyMage, a domain-specific
language and compiler for image processing pipelines. An image processing pipeline can …

Developing high-performance software is a difficult task that requires the use of low-level,
architecture-specific programming models (eg, OpenMP for CMPs, CUDA for GPUs, MPI for …

Parallel machines are becoming more complex with increasing core counts and more
heterogeneous architectures. However, the commonly used parallel programming models …

Computer systems increasingly rely on heterogeneity to achieve greater performance,
scalability and energy efficiency. Because heterogeneous systems typically comprise …

Context Software architecture viewpoints modularize the software architectures in terms of
different viewpoints that each address a different concern. Unified Modeling Language …

Many high-performance computing applications solving partial differential equations (PDEs)
can be attributed to the class of kernels using stencils on structured grids. Due to the …