Fpga Accelerated Analytics
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Fpga Accelerated Analytics
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Author : Zsolt István
language : en
Publisher:
Release Date : 2020-09-28
Fpga Accelerated Analytics written by Zsolt István and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-28 with categories.
Datacenters hosting the data-intensive applications used in machine learning and online services are facing an important challenge: the amount of data that needs to be stored and processed is increasing at an exponential rate whereas traditional processor performance has been stagnating for years as Moore's Law tapers off. Driven by these trends, data processing and management applications have become increasingly distributed leading to new data movement bottlenecks at various levels of the software and hardware architecture. The authors show how specialized hardware accelerators can provide an answer to the compute stagnation problem and be helpful in reducing data movement bottlenecks by placing them in the right location within the computer architecture. They concentrate on Field Programmable Gate Arrays (FPGAs) and show how they make it possible to express algorithms in ways that are fundamentally different from CPUs or GPUs. Many major companies are using these accelerator techniques in their storage and processing offerings. The authors discuss the benefits of using FPGAs in the context of analytical processing, both as an accelerator within a single node database and as part of distributed data analytics pipelines. They present guidelines for accelerator design in both scenarios and examples of integration within full-fledged Relational Databases. They do so through the prism of recent research projects that explore how emerging compute-intensive operations in databases can benefit from FPGAs. Finally, they highlight future research challenges in programmability and integration and cover architectural trends that are propelling the rapid adoption of accelerators in datacenters and the cloud. The monograph provides researchers and practitioners a concise insight into how FPGAs can play an important role in designing modern data-intensive computing systems. Drawing on both theory and practical implementations the readers are brought quickly up to speed on a technique that will significantly improve a system's performance.
Column Storage For Fpga Accelerated Data Analytics
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Author : David Sidler
language : en
Publisher:
Release Date : 2013
Column Storage For Fpga Accelerated Data Analytics written by David Sidler and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
Hardware Acceleration Of Video Analytics On Fpga Using Opencl
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Author : Akshay Dua
language : en
Publisher:
Release Date : 2019
Hardware Acceleration Of Video Analytics On Fpga Using Opencl written by Akshay Dua and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Gate array circuits categories.
With the exponential growth in video content over the period of the last few years, analysis of videos is becoming more crucial for many applications such as self-driving cars, healthcare, and traffic management. Most of these video analysis application uses deep learning algorithms such as convolution neural networks (CNN) because of their high accuracy in object detection. Thus enhancing the performance of CNN models become crucial for video analysis. CNN models are computationally-expensive operations and often require high-end graphics processing units (GPUs) for acceleration. However, for real-time applications in an energy-thermal constrained environment such as traffic management, GPUs are less preferred because of their high power consumption, limited energy efficiency. They are challenging to fit in a small place. To enable real-time video analytics in emerging large scale Internet of things (IoT) applications, the computation must happen at the network edge (near the cameras) in a distributed fashion. Thus, edge computing must be adopted. Recent studies have shown that field-programmable gate arrays (FPGAs) are highly suitable for edge computing due to their architecture adaptiveness, high computational throughput for streaming processing, and high energy efficiency. This thesis presents a generic OpenCL-defined CNN accelerator architecture optimized for FPGA-based real-time video analytics on edge. The proposed CNN OpenCL kernel adopts a highly pipelined and parallelized 1-D systolic array architecture, which explores both spatial and temporal parallelism for energy efficiency CNN acceleration on FPGAs. The large fan-in and fan-out of computational units to the memory interface are identified as the limiting factor in existing designs that causes scalability issues, and solutions are proposed to resolve the issue with compiler automation. The proposed CNN kernel is highly scalable and parameterized by three architecture parameters, namely pe_num, reuse_fac, and vec_fac, which can be adapted to achieve 100% utilization of the coarse-grained computation resources (e.g., DSP blocks) for a given FPGA. The proposed CNN kernel is generic and can be used to accelerate a wide range of CNN models without recompiling the FPGA kernel hardware. The performance of Alexnet, Resnet-50, Retinanet, and Light-weight Retinanet has been measured by the proposed CNN kernel on Intel Arria 10 GX1150 FPGA. The measurement result shows that the proposed CNN kernel, when mapped with 100% utilization of computation resources, can achieve a latency of 11ms, 84ms, 1614.9ms, and 990.34ms for Alexnet, Resnet-50, Retinanet, and Light-weight Retinanet respectively when the input feature maps and weights are represented using 32-bit floating-point data type.
Fpga Based Hardware Accelerators
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Author : Iouliia Skliarova
language : en
Publisher: Springer
Release Date : 2019-05-30
Fpga Based Hardware Accelerators written by Iouliia Skliarova and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-30 with Technology & Engineering categories.
This book suggests and describes a number of fast parallel circuits for data/vector processing using FPGA-based hardware accelerators. Three primary areas are covered: searching, sorting, and counting in combinational and iterative networks. These include the application of traditional structures that rely on comparators/swappers as well as alternative networks with a variety of core elements such as adders, logical gates, and look-up tables. The iterative technique discussed in the book enables the sequential reuse of relatively large combinational blocks that execute many parallel operations with small propagation delays. For each type of network discussed, the main focus is on the step-by-step development of the architectures proposed from initial concepts to synthesizable hardware description language specifications. Each type of network is taken through several stages, including modeling the desired functionality in software, the retrieval and automatic conversion of key functions, leading to specifications for optimized hardware modules. The resulting specifications are then synthesized, implemented, and tested in FPGAs using commercial design environments and prototyping boards. The methods proposed can be used in a range of data processing applications, including traditional sorting, the extraction of maximum and minimum subsets from large data sets, communication-time data processing, finding frequently occurring items in a set, and Hamming weight/distance counters/comparators. The book is intended to be a valuable support material for university and industrial engineering courses that involve FPGA-based circuit and system design.
Fpga Based Accelerators For Financial Applications
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Author : Christian De Schryver
language : en
Publisher: Springer
Release Date : 2015-07-30
Fpga Based Accelerators For Financial Applications written by Christian De Schryver and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-30 with Technology & Engineering categories.
This book covers the latest approaches and results from reconfigurable computing architectures employed in the finance domain. So-called field-programmable gate arrays (FPGAs) have already shown to outperform standard CPU- and GPU-based computing architectures by far, saving up to 99% of energy depending on the compute tasks. Renowned authors from financial mathematics, computer architecture and finance business introduce the readers into today’s challenges in finance IT, illustrate the most advanced approaches and use cases and present currently known methodologies for integrating FPGAs in finance systems together with latest results. The complete algorithm-to-hardware flow is covered holistically, so this book serves as a hands-on guide for IT managers, researchers and quants/programmers who think about integrating FPGAs into their current IT systems.
Fpga Accelerated Simulation Of Computer Systems
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Author : Hari Angepat
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Fpga Accelerated Simulation Of Computer Systems written by Hari Angepat and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Technology & Engineering categories.
To date, the most common form of simulators of computer systems are software-based running on standard computers. One promising approach to improve simulation performance is to apply hardware, specifically reconfigurable hardware in the form of field programmable gate arrays (FPGAs). This manuscript describes various approaches of using FPGAs to accelerate software-implemented simulation of computer systems and selected simulators that incorporate those techniques. More precisely, we describe a simulation architecture taxonomy that incorporates a simulation architecture specifically designed for FPGA accelerated simulation, survey the state-of-the-art in FPGA-accelerated simulation, and describe in detail selected instances of the described techniques. Table of Contents: Preface / Acknowledgments / Introduction / Simulator Background / Accelerating Computer System Simulators with FPGAs / Simulation Virtualization / Categorizing FPGA-based Simulators / Conclusion / Bibliography / Authors' Biographies
Data Processing On Fpgas
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Author : Jens Teubner
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Data Processing On Fpgas written by Jens Teubner and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
Roughly a decade ago, power consumption and heat dissipation concerns forced the semiconductor industry to radically change its course, shifting from sequential to parallel computing. Unfortunately, improving performance of applications has now become much more difficult than in the good old days of frequency scaling. This is also affecting databases and data processing applications in general, and has led to the popularity of so-called data appliances—specialized data processing engines, where software and hardware are sold together in a closed box. Field-programmable gate arrays (FPGAs) increasingly play an important role in such systems. FPGAs are attractive because the performance gains of specialized hardware can be significant, while power consumption is much less than that of commodity processors. On the other hand, FPGAs are way more flexible than hard-wired circuits (ASICs) and can be integrated into complex systems in many different ways, e.g., directly in the network for a high-frequency trading application. This book gives an introduction to FPGA technology targeted at a database audience. In the first few chapters, we explain in detail the inner workings of FPGAs. Then we discuss techniques and design patterns that help mapping algorithms to FPGA hardware so that the inherent parallelism of these devices can be leveraged in an optimal way. Finally, the book will illustrate a number of concrete examples that exploit different advantages of FPGAs for data processing. Table of Contents: Preface / Introduction / A Primer in Hardware Design / FPGAs / FPGA Programming Models / Data Stream Processing / Accelerated DB Operators / Secure Data Processing / Conclusions / Bibliography / Authors' Biographies / Index
A Streaming Accelerator For Heterogeneous Multicore Fpga Processing Of Graph Analytics Applications
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Author : Francis O'Brien
language : en
Publisher:
Release Date : 2020
A Streaming Accelerator For Heterogeneous Multicore Fpga Processing Of Graph Analytics Applications written by Francis O'Brien and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
This work explores the acceleration of graph processing on a heterogeneous platform that tightly integrates an FPGA with a multicore processor to share system memory. The key research challenge addressed is that of designing an accelerator that exclusively accesses graph data in system memory, enabling the concurrent use of both the accelerator and software. Specifically, the work proposes a streaming accelerator design for the scatter phase of iterative scatter-gather graph processing. The streaming design is implemented and evaluated on the second-generation Intel Heterogeneous Architecture Research Platform (HARPv2). Evaluation of three key graph processing kernels using a combination of synthetic and real-world graphs shows that this design achieves highperformance, up to 1100 MTEPS. Further, the accelerator has high FPGA-to-Memory bandwidth utilization, over 90%. The streaming accelerator also features fine-grain granularity sharing with the CPU that enables integration with efficient load-balancing schemes, such as work-stealing.
Large Scale Transactional Execution Of Fpga Accelerated Irregular Applications
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Author : Xiaoyu Ma (Ph. D.)
language : en
Publisher:
Release Date : 2017
Large Scale Transactional Execution Of Fpga Accelerated Irregular Applications written by Xiaoyu Ma (Ph. D.) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Irregular workloads are programs organized around pointer-based data structures ctures such as graphs. They are widely used in many fields such as computer/human network analysis, machine learning, data mining, graphics, electronic design automation, and so on. Many irregular applications have massive data-level parallelism because they iterate over a large number of graph nodes or edges using the same operators. This dissertation proposes large-scale transactional execution, as well as an architecture to achieve this approach. We apply this approach to irregular applications by executing a large number of graph operations concurrently and as transactions to deal with potential conflicts. Before this work, large-scale transactional execution was generally considered impractical because doing so might incur too many conflicts that would negate the potential benefits of the parallelization. We propose a set of techniques to address the high conflict issue and argue that given the large size and topology of many modern graphs, large-scale, multi-threaded, transactional execution can provide performance, energy efficiency, and programability benefits. We present challenges of realizing such an architecture, including the requirement of scalable conflict detection, livelock avoidance and transactional state overflow handling, and propose solutions. While the proposed techniques are also applicable to CPUs and ASICs, we focus on using FPGAs and implement the proposed architecture as a synthesizable FPGA RTL design. We compare our implementation in performance and energy efficiency against an Intel Haswell-based baseline platform. In addition, we perform an extensive study of various micro-architectural design choices in large-scale transactional execution architecture and evaluate their impact on performance. Finally, we explore the use of fine-grained locks to replace transactions to further improve performance.
Security Of Fpga Accelerated Cloud Computing Environments
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Author : Jakub Szefer
language : en
Publisher: Springer Nature
Release Date : 2024-01-29
Security Of Fpga Accelerated Cloud Computing Environments written by Jakub Szefer and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-29 with Technology & Engineering categories.
This book addresses security of FPGA-accelerated cloud computing environments. It presents a comprehensive review of the state-of-the-art in security threats as well as defenses. The book further presents design principles to help in the evaluation and designs of cloud-based FPGA deployments which are secure from information leaks and potential attacks.