On Designing Multicore-aware Simulators for Biological Systems

The stochastic simulation of biological systems is an increasingly popular technique in bioinformatics. It often is an enlightening technique, which may however result in being computational expensive. We discuss the main opportunities to speed it up on multi-core platforms, which pose new challenges for parallelisation techniques. These opportunities are developed in two general families of solutions involving both the single simulation and a bulk of independent simulations (either replicas of derived from parameter sweep). Proposed solutions are tested on the parallelisation of the CWC simulator (Calculus of Wrapped Compartments) that is carried out according to proposed solutions by way of the FastFlow programming framework making possible fast development and efficient execution on multi-cores.Comment: 19 pages + cover pag

Parallel symbolic state-space exploration is difficult, but what is the alternative?

State-space exploration is an essential step in many modeling and analysis problems. Its goal is to find the states reachable from the initial state of a discrete-state model described. The state space can used to answer important questions, e.g., "Is there a dead state?" and "Can N become negative?", or as a starting point for sophisticated investigations expressed in temporal logic. Unfortunately, the state space is often so large that ordinary explicit data structures and sequential algorithms cannot cope, prompting the exploration of (1) parallel approaches using multiple processors, from simple workstation networks to shared-memory supercomputers, to satisfy large memory and runtime requirements and (2) symbolic approaches using decision diagrams to encode the large structured sets and relations manipulated during state-space generation. Both approaches have merits and limitations. Parallel explicit state-space generation is challenging, but almost linear speedup can be achieved; however, the analysis is ultimately limited by the memory and processors available. Symbolic methods are a heuristic that can efficiently encode many, but not all, functions over a structured and exponentially large domain; here the pitfalls are subtler: their performance varies widely depending on the class of decision diagram chosen, the state variable order, and obscure algorithmic parameters. As symbolic approaches are often much more efficient than explicit ones for many practical models, we argue for the need to parallelize symbolic state-space generation algorithms, so that we can realize the advantage of both approaches. This is a challenging endeavor, as the most efficient symbolic algorithm, Saturation, is inherently sequential. We conclude by discussing challenges, efforts, and promising directions toward this goal

SPar: A DSL for High-Level and Productive Stream Parallelism

This paper introduces SPar, an internal C++ Domain-Specific Language (DSL) that supports the development of classic stream parallel applications. The DSL uses standard C++ attributes to introduce annotations tagging the notable components of stream parallel applications: stream sources and stream processing stages. A set of tools process SPar code (C++ annotated code using the SPar attributes) to generate FastFlow C++ code that exploits the stream parallelism denoted by SPar annotations while targeting shared memory multi-core architectures. We outline the main SPar features along with the main implementation techniques and tools. Also, we show the results of experiments assessing the feasibility of the entire approach as well as SPar's performance and expressiveness

Parallel visual data restoration on multi-GPGPUs using stencil-reduce pattern

In this paper, a highly effective parallel filter for visual data restoration is presented. The filter is designed following a skeletal approach, using a newly proposed stencil-reduce, and has been implemented by way of the FastFlow parallel programming library. As a result of its high-level design, it is possible to run the filter seamlessly on a multicore machine, on multi-GPGPUs, or on both. The design and implementation of the filter are discussed, and an experimental evaluation is presented

Nanowrinkled Carbon Aerogels Embedded with FeN x Sites as Effective Oxygen Electrodes for Rechargeable Zinc-Air Battery.

Rational design of single-metal atom sites in carbon substrates by a flexible strategy is highly desired for the preparation of high-performance catalysts for metal-air batteries. In this study, biomass hydrogel reactors are utilized as structural templates to prepare carbon aerogels embedded with single iron atoms by controlled pyrolysis. The tortuous and interlaced hydrogel chains lead to the formation of abundant nanowrinkles in the porous carbon aerogels, and single iron atoms are dispersed and stabilized within the defective carbon skeletons. X-ray absorption spectroscopy measurements indicate that the iron centers are mostly involved in the coordination structure of FeN4, with a minor fraction (ca. 1/5) in the form of FeN3C. First-principles calculations show that the FeN x sites in the Stone-Wales configurations induced by the nanowrinkles of the hierarchically porous carbon aerogels show a much lower free energy than the normal counterparts. The resulting iron and nitrogen-codoped carbon aerogels exhibit excellent and reversible oxygen electrocatalytic activity, and can be used as bifunctional cathode catalysts in rechargeable Zn-air batteries, with a performance even better than that based on commercial Pt/C and RuO2 catalysts. Results from this study highlight the significance of structural distortions of the metal sites in carbon matrices in the design and engineering of highly active single-atom catalysts

A Multicamera System for Gesture Tracking With Three Dimensional Hand Pose Estimation

The goal of any visual tracking system is to successfully detect then follow an object of interest through a sequence of images. The difficulty of tracking an object depends on the dynamics, the motion and the characteristics of the object as well as on the environ ment. For example, tracking an articulated, self-occluding object such as a signing hand has proven to be a very difficult problem. The focus of this work is on tracking and pose estimation with applications to hand gesture interpretation. An approach that attempts to integrate the simplicity of a region tracker with single hand 3D pose estimation methods is presented. Additionally, this work delves into the pose estimation problem. This is ac complished by both analyzing hand templates composed of their morphological skeleton, and addressing the skeleton\u27s inherent instability. Ligature points along the skeleton are flagged in order to determine their effect on skeletal instabilities. Tested on real data, the analysis finds the flagging of ligature points to proportionally increase the match strength of high similarity image-template pairs by about 6%. The effectiveness of this approach is further demonstrated in a real-time multicamera hand tracking system that tracks hand gestures through three-dimensional space as well as estimate the three-dimensional pose of the hand