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High-Performance Computing (HPC) delivers higher computational performance to solve problems in science, engineering and finance. There are various HPC resources available for different needs, ranging from cloud computing– that can be used without much expertise and expense – to more tailored hardware, such as Field-Programmable Gate Arrays (FPGAs) or D-Wave’s quantum computer systems. High-Performance Computing in Finance is the first book that provides a state-of-the-art introduction to HPC for finance, capturing both academically and practically relevant problems.
High-Performance Computing (HPC) delivers higher computational performance to solve problems in science, engineering and finance. There are various HPC resources available for different needs, ranging from cloud computing– that can be used without much expertise and expense – to more tailored hardware, such as Field-Programmable Gate Arrays (FPGAs) or D-Wave’s quantum computer systems. High-Performance Computing in Finance is the first book that provides a state-of-the-art introduction to HPC for finance, capturing both academically and practically relevant problems.
High-Performance Computing using FPGA covers the area of high performance reconfigurable computing (HPRC). This book provides an overview of architectures, tools and applications for High-Performance Reconfigurable Computing (HPRC). FPGAs offer very high I/O bandwidth and fine-grained, custom and flexible parallelism and with the ever-increasing computational needs coupled with the frequency/power wall, the increasing maturity and capabilities of FPGAs, and the advent of multicore processors which has caused the acceptance of parallel computational models. The Part on architectures will introduce different FPGA-based HPC platforms: attached co-processor HPRC architectures such as the CHREC’s Novo-G and EPCC’s Maxwell systems; tightly coupled HRPC architectures, e.g. the Convey hybrid-core computer; reconfigurably networked HPRC architectures, e.g. the QPACE system, and standalone HPRC architectures such as EPFL’s CONFETTI system. The Part on Tools will focus on high-level programming approaches for HPRC, with chapters on C-to-Gate tools (such as Impulse-C, AutoESL, Handel-C, MORA-C++); Graphical tools (MATLAB-Simulink, NI LabVIEW); Domain-specific languages, languages for heterogeneous computing(for example OpenCL, Microsoft’s Kiwi and Alchemy projects). The part on Applications will present case from several application domains where HPRC has been used successfully, such as Bioinformatics and Computational Biology; Financial Computing; Stencil computations; Information retrieval; Lattice QCD; Astrophysics simulations; Weather and climate modeling.
In this fast-paced global economy, academia and industry must innovate to evolve and succeed. Today’s researchers and industry experts are seeking transformative technologies to meet the challenges of tomorrow. Cutting-edge technological advances in cybersecurity solutions aid in enabling the security of complex heterogeneous high-performance computing (HPC) environments. On the other hand, HPC facilitates powerful and intelligent innovative models for reducing time to response to identify and resolve a multitude of potential, newly emerging cyberattacks. Cybersecurity and High-Performance Computing Environments provides a collection of the current and emergent research innovations, practices, and applications focusing on the interdependence of cybersecurity and HPC domains for discovering and resolving new emerging cyber-threats. KEY FEATURES Represents a substantial research contribution to the state-of-the-art solutions for addressing the threats to confidentiality, integrity, and availability (CIA triad) in HPC environments Covers the groundbreaking and emergent solutions that utilize the power of the HPC environments to study and understand the emergent, multifaceted, anomalous, and malicious characteristics The content will help university students, researchers, and professionals understand how HPC research fits broader cybersecurity objectives and vice versa.
Proceedings -- Parallel Computing.
This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications.
This book constitutes the refereed joint proceedings of ten international workshops held in conjunction with the 4th International Symposium on Parallel and Distributed Processing and Applications, ISPA 2006, held in Sorrento, Italy in December 2006. It contains 116 papers that contribute to enlarging the spectrum of the more general topics treated in the ISPA 2006 main conference.
An in-depth guide covering system architecture, low-latency strategies, risk management, and machine learning for experienced programmers looking to enter the financial industry and build high-performance trading systems Key Features Get started with building financial trading systems Focus on scalability, architecture, and implementing low-latency network communication in C++ Optimize code and use parallel computing techniques for better performance Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionUnlock the secrets of the finance industry and dive into the world of high-performance trading systems with C++ High Performance for Financial Systems. Trading systems are the backbone of the financial world, and understanding how to build them for optimal performance is crucial for success. If you've ever dreamt of creating scalable and cutting-edge financial software, this guide is your key to success. A cornerstone of this book is its coverage of system design and architecture. The book starts by outlining the role of C++ in finance and trading. You'll learn the principles and methodologies behind building systems that can handle vast amounts of data, execute complex trading strategies with ease, and maintain the highest levels of reliability. Armed with this knowledge, you'll be equipped to tackle even the most challenging trading scenarios. In the fast-paced world of finance, every millisecond counts. This book delves into low-latency strategies that will enable your trading systems to react with lightning speed. You’ll also learn the art of reducing latency, optimizing code, and leveraging the latest hardware and software techniques to gain a competitive edge in the market. By the end of this book, you’ll be well-versed in architecting a financial trading system as well as advanced strategies and new industry trends.What you will learn Design architecture for scalable financial trading systems Understand strategies for low-latency trading and high-frequency trading Discover how to implement machine learning algorithms for financial data analysis Understand risk management techniques for financial trading systems Explore advanced topics in finance and trading, including machine learning for algorithmic trading and portfolio optimization Get up to speed with best practices for developing financial trading systems with C++ Who this book is for This book is for experienced C++ developers who want to enter the finance industry and learn how trading systems work. It is also suitable for quantitative analysts, financial engineers, and anyone interested in building scalable and robust trading systems. The book assumes familiarity with the C++ programming language, data structures, and algorithms. Additionally, readers should have a basic understanding of finance and trading concepts, such as market data, trading strategies, and risk management.
Performance Computing: Modern Systems and Practices is a fully comprehensive and easily accessible treatment of high performance computing, covering fundamental concepts and essential knowledge while also providing key skills training. With this book, students will begin their careers with an understanding of possible directions for future research and development in HPC, domain scientists will learn how to use supercomputers as a key tool in their quest for new knowledge, and practicing engineers will discover how supercomputers can employ HPC systems and methods to the design and simulation of innovative products. This new edition has been fully updated, and has been reorganized and restructured to improve accessibility for undergraduate students while also adding trending content such as machine learning and a new chapter on CUDA. - Covers enabling technologies, system architectures and operating systems, parallel programming languages and algorithms, scientific visualization, correctness and performance debugging tools and methods, GPU accelerators, and big data problems - Provides numerous examples that explore the basics of supercomputing while also providing practical training in the real use of high-end computers - Helps users with informative and practical examples that build knowledge and skills through incremental steps - Features sidebars of background and context to present a live history and culture of this unique field
This is a textbook that teaches the bridging topics between numerical analysis, parallel computing, code performance, large scale applications.