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Annotation International Symposium on Symbolic and Numeric Algorithms for Scientific Computing is an international conference that aims to stimulate the interaction between the two scientific communities of symbolic and numeric computing and to exhibit interesting applications of the areas both in theory and in practice.

Computer algorithms

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Novel scalable scientific algorithms are needed in order to enable key science applications to exploit the computational power of large-scale systems. This is especially true for the current tier of leading petascale machines and the road to exascale computing as HPC systems continue to scale up in compute node and processor core count. These extreme-scale systems require novel scientific algorithms to hide network and memory latency, have very high computation/communication overlap, have minimal communication, and have no synchronization points. With the advent of Big Data in the past few years the need of such scalable mathematical methods and algorithms able to handle data and compute intensive applications at scale becomes even more important. Scientific algorithms for multi-petaflop and exa-flop systems also need to be fault tolerant and fault resilient, since the probability of faults increases with scale. Resilience at the system software and at the algorithmic level is needed as a crosscutting effort. Finally, with the advent of heterogeneous compute nodes that employ standard processors as well as GPGPUs, scientific algorithms need to match these architectures to extract the most performance. This includes different system-specific levels of parallelism as well as co-scheduling of computation. Key science applications require novel mathematics and mathematical models and system software that address the scalability and resilience challenges of current- and future-generation extreme-scale HPC systems. The goal of this workshop is to bring together experts in the area of scalable algorithms to present the latest achievements and to discuss the challenges ahead.

Computer algorithms

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Nanocrystals. --- Voronoi polygons. --- Algorithms.

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Nanocrystals. --- Voronoi polygons. --- Algorithms.

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"Derivatives Algorithms — Volume 1: Bones (Second Edition) is for practicing quants who already have some expertise in risk-neutral pricing and in programming, and want to build a reusable and extensible library. Rather than specific models, this volume provides foundations common to all pricing, such as C++ code structure, interfaces, and several widely used mathematical methods. It also presents a set of protocols, by which models and trades can collaborate to support pricing and hedging tasks, and illustrates their use with several example trade types and models. Readers will learn to deploy the results of their research work with productivity-enhancing methods that are not taught elsewhere, including object serialization, code generation, and separation of concerns for continuous improvement. Of all the books on derivatives pricing, only Derivatives Algorithms shows the internals of a high-quality working library. The new Second Edition is more accessible to readers who are not already familiar with the book's concepts; there is an increased focus on explaining the motivation for each step, and on providing a high-level perspective on design choices. The chapters on Persistence and Protocols have been substantially rewritten, providing motivating examples and additional detail in the code. The treatment of yield curves and funding has been modernized, with the increased sophistication required by today's markets. And a new final chapter, describing the next phase in the evolution of derivatives valuation and risk, has been added."--

Derivative securities --- Algorithms --- Data processing.