SBLOCK: A framework for efficient stencil-based PDE solvers on multi-core platforms

We present a new software framework for the implementation of applications that use stencil computations on block-structured grids to solve partial differential equations. A key feature of the framework is the extensive use of automatic source code generation which is used to achieve high performance on a range of leading multi-core processors. Results are presented for a simple model stencil running on Intel and AMD CPUs as well as the NVIDIA GT200 GPU. The generality of the framework is demonstrated through the implementation of a complete application consisting of many different stencil computations, taken from the field of computational fluid dynamics. © 2010 IEEE.

BarraCUDA - a fast short read sequence aligner using graphics processing units.

BACKGROUND: With the maturation of next-generation DNA sequencing (NGS) technologies, the throughput of DNA sequencing reads has soared to over 600 gigabases from a single instrument run. General purpose computing on graphics processing units (GPGPU), extracts the computing power from hundreds of parallel stream processors within graphics processing cores and provides a cost-effective and energy efficient alternative to traditional high-performance computing (HPC) clusters. In this article, we describe the implementation of BarraCUDA, a GPGPU sequence alignment software that is based on BWA, to accelerate the alignment of sequencing reads generated by these instruments to a reference DNA sequence. FINDINGS: Using the NVIDIA Compute Unified Device Architecture (CUDA) software development environment, we ported the most computational-intensive alignment component of BWA to GPU to take advantage of the massive parallelism. As a result, BarraCUDA offers a magnitude of performance boost in alignment throughput when compared to a CPU core while delivering the same level of alignment fidelity. The software is also capable of supporting multiple CUDA devices in parallel to further accelerate the alignment throughput. CONCLUSIONS: BarraCUDA is designed to take advantage of the parallelism of GPU to accelerate the alignment of millions of sequencing reads generated by NGS instruments. By doing this, we could, at least in part streamline the current bioinformatics pipeline such that the wider scientific community could benefit from the sequencing technology.BarraCUDA is currently available from http://seqbarracuda.sf.net.

Binder free three-dimensional sulphur/few-layer graphene foam cathode with enhanced high-rate capability for rechargeable lithium sulphur batteries.

A novel ultra-lightweight three-dimensional (3-D) cathode system for lithium sulphur (Li-S) batteries has been synthesised by loading sulphur on to an interconnected 3-D network of few-layered graphene (FLG) via a sulphur solution infiltration method. A free-standing FLG monolithic network foam was formed as a negative of a Ni metallic foam template by CVD followed by etching away of Ni. The FLG foam offers excellent electrical conductivity, an appropriate hierarchical pore structure for containing the electro-active sulphur and facilitates rapid electron/ion transport. This cathode system does not require any additional binding agents, conductive additives or a separate metallic current collector thus decreasing the weight of the cathode by typically ∼20-30 wt%. A Li-S battery with the sulphur-FLG foam cathode shows good electrochemical stability and high rate discharge capacity retention for up to 400 discharge/charge cycles at a high current density of 3200 mA g(-1). Even after 400 cycles the capacity decay is only ∼0.064% per cycle relative to the early (e.g. the 5th cycle) discharge capacity, while yielding an average columbic efficiency of ∼96.2%. Our results indicate the potential suitability of graphene foam for efficient, ultra-light and high-performance batteries.