The GPU vs Phi Debate: Risk Analytics Using Many-Core Computing

The risk of reinsurance portfolios covering globally occurring natural catastrophes, such as earthquakes and hurricanes, is quantified by employing simulations. These simulations are computationally intensive and require large amounts of data to be processed. The use of many-core hardware accelerators, such as the Intel Xeon Phi and the NVIDIA Graphics Processing Unit (GPU), are desirable for achieving high-performance risk analytics. In this paper, we set out to investigate how accelerators can be employed in risk analytics, focusing on developing parallel algorithms for Aggregate Risk Analysis, a simulation which computes the Probable Maximum Loss of a portfolio taking both primary and secondary uncertainties into account. The key result is that both hardware accelerators are useful in different contexts; without taking data transfer times into account the Phi had lowest execution times when used independently and the GPU along with a host in a hybrid platform yielded best performance.Comment: A modified version of this article is accepted to the Computers and Electrical Engineering Journal under the title - "The Hardware Accelerator Debate: A Financial Risk Case Study Using Many-Core Computing"; Blesson Varghese, "The Hardware Accelerator Debate: A Financial Risk Case Study Using Many-Core Computing," Computers and Electrical Engineering, 201

Part 1: a process view of nature. Multifunctional integration and the role of the construction agent

This is the first of two linked articles which draw s on emerging understanding in the field of biology and seeks to communicate it to those of construction, engineering and design. Its insight is that nature 'works' at the process level, where neither function nor form are distinctions, and materialisation is both the act of negotiating limited resource and encoding matter as 'memory', to sustain and integrate processes through time. It explores how biological agents derive work by creating 'interfaces' between adjacent locations as membranes, through feedback. Through the tension between simultaneous aggregation and disaggregation of matter by agents with opposing objectives, many functions are integrated into an interface as it unfolds. Significantly, biological agents induce flow and counterflow conditions within biological interfaces, by inducing phase transition responses in the matte r or energy passing through them, driving steep gradients from weak potentials (i.e. shorter distances and larger surfaces). As with biological agents, computing, programming and, increasingly digital sensor and effector technologies share the same 'agency' and are thus convergent

Modelling the formation of ordered acentrosomal microtubule arrays

Acentrosomal microtubules are not bound to a microtubule organising centre yet are still able to form ordered arrays. Two clear examples of this behaviour are the acentrosomal apico-basal (side wall) array in epithelial cells and the parallel organisation of plant cortical microtubules. This research investigates their formation through mathematical modelling and Monte Carlo simulations with the software programs developed ourselves. In epithelial cells there is a generally accepted `release and capture' hypothesis for the transfer of centrosomal microtubules onto the side wall array. We use a combination of mathematical and Monte Carlo simulation models to perform the first modelling of this hypothesis. We find that a tubulin concentration dependent dynamic instability is not a good�fit to this hypothesis but that a reduced centrosomal nucleation rate in response to an increased number of side wall microtubules makes the hypothesis work in biologically reasonable conditions. We propose that the loss of nucleation rate is a result of ninein being transferred from the centrosome to the side wall. We show OpenCL to be a useful tool in building a simulation program for parameter searches. We use a Monte Carlo simulation model to investigate how the collision induced catastrophe (CIC) probability affects the formation of the ordered array of cortical plant microtubules. We find that with entrainment an ordered array stops forming once the CIC drops below 0.5. We�find that the severing action of katanin is able to restore order at CIC probabilities below 0.5 but the speed at which crossovers must be severed becomes unfeasibly fast as the CIC decreases. This implies that at very low CICs observed in nature (�0.1), katanin may be necessary but not suffi�cient to create the ordered array. We also provide a customisable and intuitive cortical microtubule simulation software to aid in further research

N-body simulations of gravitational dynamics

We describe the astrophysical and numerical basis of N-body simulations, both of collisional stellar systems (dense star clusters and galactic centres) and collisionless stellar dynamics (galaxies and large-scale structure). We explain and discuss the state-of-the-art algorithms used for these quite different regimes, attempt to give a fair critique, and point out possible directions of future improvement and development. We briefly touch upon the history of N-body simulations and their most important results.Comment: invited review (28 pages), to appear in European Physics Journal Plu

Network Partitioning in Distributed Agent-Based Models

Agent-Based Models (ABMs) are an emerging simulation paradigm for modeling complex systems, comprised of autonomous, possibly heterogeneous, interacting agents. The utility of ABMs lies in their ability to represent such complex systems as self-organizing networks of agents. Modeling and understanding the behavior of complex systems usually occurs at large and representative scales, and often obtaining and visualizing of simulation results in real-time is critical. The real-time requirement necessitates the use of in-memory computing, as it is difficult and challenging to handle the latency and unpredictability of disk accesses. Combining this observation with the scale requirement emphasizes the need to use parallel and distributed computing platforms, such as MPI-enabled CPU clusters. Consequently, the agent population must be partitioned across different CPUs in a cluster. Further, the typically high volume of interactions among agents can quickly become a significant bottleneck for real-time or large-scale simulations. The problem is exacerbated if the underlying ABM network is dynamic and the inter-process communication evolves over the course of the simulation. Therefore, it is critical to develop topology-aware partitioning mechanisms to support such large simulations. In this dissertation, we demonstrate that distributed agent-based model simulations benefit from the use of graph partitioning algorithms that involve a local, neighborhood-based perspective. Such methods do not rely on global accesses to the network and thus are more scalable. In addition, we propose two partitioning schemes that consider the bottom-up individual-centric nature of agent-based modeling. The First technique utilizes label-propagation community detection to partition the dynamic agent network of an ABM. We propose a latency-hiding, seamless integration of community detection in the dynamics of a distributed ABM. To achieve this integration, we exploit the similarity in the process flow patterns of a label-propagation community-detection algorithm and self-organizing ABMs. In the second partitioning scheme, we apply a combination of the Guided Local Search (GLS) and Fast Local Search (FLS) metaheuristics in the context of graph partitioning. The main driving principle of GLS is the dynamic modi?cation of the objective function to escape local optima. The algorithm augments the objective of a local search, thereby transforming the landscape structure and escaping a local optimum. FLS is a local search heuristic algorithm that is aimed at reducing the search space of the main search algorithm. It breaks down the space into sub-neighborhoods such that inactive sub-neighborhoods are removed from the search process. The combination of GLS and FLS allowed us to design a graph partitioning algorithm that is both scalable and sensitive to the inherent modularity of real-world networks

Modeling Earthquakes via Computer Programs

Modeling earthquakes plays an important role in investigation of different aspects of seismic risk. The paper continues previous studies and describes the user-friendly software destined for numerical simulation of lithosphere dynamics and seismicity by means of different modifications of the block model, which exploits the hierarchical block structure of the lithosphere. As a result, the model produces an earthquake catalog, and the programs give an opportunity to visualize it in different ways. The programs work in an interactive mode with a window interface. Numerical approximation of the Vrancea seismic region is considered as an example of application of the software. Parallel algorithms allowing to perform modeling dynamics of rather large structures are outlined

Institute for Computational Mechanics in Propulsion (ICOMP) fourth annual review, 1989

The Institute for Computational Mechanics in Propulsion (ICOMP) is operated jointly by Case Western Reserve University and the NASA Lewis Research Center. The purpose of ICOMP is to develop techniques to improve problem solving capabilities in all aspects of computational mechanics related to propulsion. The activities at ICOMP during 1989 are described

Multi-Tenant Virtual GPUs for Optimising Performance of a Financial Risk Application

Graphics Processing Units (GPUs) are becoming popular accelerators in modern High-Performance Computing (HPC) clusters. Installing GPUs on each node of the cluster is not efficient resulting in high costs and power consumption as well as underutilisation of the accelerator. The research reported in this paper is motivated towards the use of few physical GPUs by providing cluster nodes access to remote GPUs on-demand for a financial risk application. We hypothesise that sharing GPUs between several nodes, referred to as multi-tenancy, reduces the execution time and energy consumed by an application. Two data transfer modes between the CPU and the GPUs, namely concurrent and sequential, are explored. The key result from the experiments is that multi-tenancy with few physical GPUs using sequential data transfers lowers the execution time and the energy consumed, thereby improving the overall performance of the application.Comment: Accepted to the Journal of Parallel and Distributed Computing (JPDC), 10 June 201