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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.
Revolutionize your financial advisory practice with the latest cutting-edge tools Tired of spending more time with filing cabinets than with clients? Is overhead eating up your margins? In a new revised edition of the "bible" of practice management and technology for financial professionals, two leading financial planners, with some help from their friends*, deliver the knowledge advisors have been begging for. This book serves up a nontechnical trove of technology, clever workarounds, and procedural efficiencies tailored to help financial advisors in private practice move toward today's virtual office. The authors show you how to drastically reduce the paperwork in your office, slash overhead, and find anything you need in seconds using the latest software. This revised edition includes new information on SaaS and cloud computing, software integrations, mobile devices/apps, social media tools, portfolio accounting and outsourcing, collaborative tools, digital signatures, workflow management, marketing technology and much more. Perfect for successful practices seeking greater efficiencies and healthier profit margins The authors are well-known financial advisors, each with more than 30 years of experience in financial services Addresses the evolution of the virtual office and its impact on advisory firms If you're looking for new systems and efficiencies to transform and streamline your private practice, look no further than Technology Tools for Today's High-Margin Practice. *Chapter 1 Selecting the Right CRM System, Davis D. Janowski Chapter 2 The Future of Financial Planning Software, Bob Curtis Chapter 3 The Future of Financial Planning Software and the New Client-Advisor Relationship, Linda Strachan Chapter 4 Portfolio Management Software, Mike Kelly Chapter 5 Achieving Growth and Profitability with Technology Integration, Jon Patullo Chapter 6 How the World Wide Web Impacts the Financial Advisor, Bart Wisniowski Chapter 7 Managing Your Online Presence, Marie Swift Chapter 8 Client Portals and Collaboration, Bill Winterberg Chapter 9 The Cloud, J. D. Bruce Chapter 10 Digital Signature Technology, Dan Skiles Chapter 11 Innovative Software and Technologies Implemented at One of the United States’ Leading Advisory Firms, Louis P. Stanasolovich Chapter 12 Virtual Staff Sparks Growth, Profitability, and Scalability, Jennifer Goldman Chapter 13 ROI—The Holy Grail of the Technology Purchase Decision, Timothy D. Welsh Chapter 14 Building an Efficient Workflow Management System, David L. Lawrence
This book explores energy efficiency techniques for high-performance computing (HPC) systems using power-management methods. Adopting a step-by-step approach, it describes power-management flows, algorithms and mechanism that are employed in modern processors such as Intel Sandy Bridge, Haswell, Skylake and other architectures (e.g. ARM). Further, it includes practical examples and recent studies demonstrating how modem processors dynamically manage wide power ranges, from a few milliwatts in the lowest idle power state, to tens of watts in turbo state. Moreover, the book explains how thermal and power deliveries are managed in the context this huge power range. The book also discusses the different metrics for energy efficiency, presents several methods and applications of the power and energy estimation, and shows how by using innovative power estimation methods and new algorithms modern processors are able to optimize metrics such as power, energy, and performance. Different power estimation tools are presented, including tools that break down the power consumption of modern processors at sub-processor core/thread granularity. The book also investigates software, firmware and hardware coordination methods of reducing power consumption, for example a compiler-assisted power management method to overcome power excursions. Lastly, it examines firmware algorithms for dynamic cache resizing and dynamic voltage and frequency scaling (DVFS) for memory sub-systems.
Since the creation of the term "Scientific Computing" and of its German counterpart "Wissenschaftliches Rechnen" (whoever has to be blamed for that), scientists from outside the field have been confused about the some what strange distinction between scientific and non-scientific computations. And the insiders, i. e. those who are, at least, convinced of always comput ing in a very scientific way, are far from being happy with this summary of their daily work, even if further characterizations like "High Performance" or "Engineering" try to make things clearer - usually with very modest suc cess, however. Moreover, to increase the unfortunate confusion of terms, who knows the differences between "Computational Science and Engineering" , as indicated in the title of the series these proceedings were given the honour to be published in, and "Scientific and Engineering Computing", as chosen for the title of our book? Actually, though the protagonists of scientific com puting persist in its independence as a scientific discipline (and rightly so, of course), the ideas behind the term diverge wildly. Consequently, the variety of answers one can get to the question "What is scientific computing?" is really impressive and ranges from the (serious) "nothing else but numerical analysis" up to the more mocking "consuming as much CPU-time as possible on the most powerful number crunchers accessible" .