Hi-C experiments explore the 3D structure of the genome, generating terabases of data to
create high-resolution contact maps. Here, we introduce Juicer, an open-source tool for …

High-performance computing has recently seen a surge of interest in heterogeneous
systems, with an emphasis on modern Graphics Processing Units (GPUs). These devices …

Due to decelerating gains in single-core CPU performance, computationally expensive
simulations are increasingly executed on highly parallel hardware platforms. Agent-based …

The Single Instruction Multiple Data (SIMD) architecture, supported by various high-
performance computing platforms, efficiently utilizes data-level parallelism. The SIMD model …

In this paper, we present the Habanero-Java (HJ) language developed at Rice University as
an extension to the original Java-based definition of the X10 language. HJ includes a …

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

The performance benefits of GPU parallelism can be enormous, but unlocking this
performance potential is challenging. The applicability and performance of GPU …

Optical nanoscopy is rapidly gaining momentum in the life sciences. Current instruments
are, however, often large and expensive, and there is a substantial delay between raw data …

MapReduce is a programming model that enables efficient massive data processing in large-
scale computing environments such as supercomputers and clouds. Such large-scale …

Recent compilers comprise an incremental way for converting software toward accelerators.
For instance, the pgi Accelerator [14] or hmpp [3] require the use of directives. The …