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Author: Yue Wang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
The other technique targets on maximizing the average throughput of all parallel processors under the dynamic power constraints. We formalize this target as a linear programming problem and solve it on the runtime. According to the simulation results, the first technique achieves more than 22% power savings with a 4% improvement in performance and the second technique saves 11% power consumption with 9% performance improvement. The contributions of this dissertation represent a significant advancement in the quest for improving performance and reducing energy consumption of GPGPU.
Author: Yue Wang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
The other technique targets on maximizing the average throughput of all parallel processors under the dynamic power constraints. We formalize this target as a linear programming problem and solve it on the runtime. According to the simulation results, the first technique achieves more than 22% power savings with a 4% improvement in performance and the second technique saves 11% power consumption with 9% performance improvement. The contributions of this dissertation represent a significant advancement in the quest for improving performance and reducing energy consumption of GPGPU.
Author: Tor M. Aamodt
Publisher: Springer Nature
ISBN: 3031017595
Category : Technology & Engineering
Languages : en
Pages : 122
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Book Description
Originally developed to support video games, graphics processor units (GPUs) are now increasingly used for general-purpose (non-graphics) applications ranging from machine learning to mining of cryptographic currencies. GPUs can achieve improved performance and efficiency versus central processing units (CPUs) by dedicating a larger fraction of hardware resources to computation. In addition, their general-purpose programmability makes contemporary GPUs appealing to software developers in comparison to domain-specific accelerators. This book provides an introduction to those interested in studying the architecture of GPUs that support general-purpose computing. It collects together information currently only found among a wide range of disparate sources. The authors led development of the GPGPU-Sim simulator widely used in academic research on GPU architectures. The first chapter of this book describes the basic hardware structure of GPUs and provides a brief overview of their history. Chapter 2 provides a summary of GPU programming models relevant to the rest of the book. Chapter 3 explores the architecture of GPU compute cores. Chapter 4 explores the architecture of the GPU memory system. After describing the architecture of existing systems, Chapters 3 and 4 provide an overview of related research. Chapter 5 summarizes cross-cutting research impacting both the compute core and memory system. This book should provide a valuable resource for those wishing to understand the architecture of graphics processor units (GPUs) used for acceleration of general-purpose applications and to those who want to obtain an introduction to the rapidly growing body of research exploring how to improve the architecture of these GPUs.
Author: Hyesoon Kim
Publisher: Morgan & Claypool Publishers
ISBN: 1608459551
Category : Computers
Languages : en
Pages : 98
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Book Description
General-purpose graphics processing units (GPGPU) have emerged as an important class of shared memory parallel processing architectures, with widespread deployment in every computer class from high-end supercomputers to embedded mobile platforms. Relative to more traditional multicore systems of today, GPGPUs have distinctly higher degrees of hardware multithreading (hundreds of hardware thread contexts vs. tens), a return to wide vector units (several tens vs. 1-10), memory architectures that deliver higher peak memory bandwidth (hundreds of gigabytes per second vs. tens), and smaller caches/scratchpad memories (less than 1 megabyte vs. 1-10 megabytes). In this book, we provide a high-level overview of current GPGPU architectures and programming models. We review the principles that are used in previous shared memory parallel platforms, focusing on recent results in both the theory and practice of parallel algorithms, and suggest a connection to GPGPU platforms. We aim to provide hints to architects about understanding algorithm aspect to GPGPU. We also provide detailed performance analysis and guide optimizations from high-level algorithms to low-level instruction level optimizations. As a case study, we use n-body particle simulations known as the fast multipole method (FMM) as an example. We also briefly survey the state-of-the-art in GPU performance analysis tools and techniques. Table of Contents: GPU Design, Programming, and Trends / Performance Principles / From Principles to Practice: Analysis and Tuning / Using Detailed Performance Analysis to Guide Optimization
Author: Matt Pharr
Publisher: Addison-Wesley Professional
ISBN: 9780321335593
Category : Computers
Languages : en
Pages : 814
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Book Description
More useful techniques, tips, and tricks for harnessing the power of the new generation of powerful GPUs.
Author: Jason Sanders
Publisher: Addison-Wesley Professional
ISBN: 0132180138
Category : Computers
Languages : en
Pages : 524
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Book Description
CUDA is a computing architecture designed to facilitate the development of parallel programs. In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of graphics processing units (GPUs) when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA now brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance. No knowledge of graphics programming is required—just the ability to program in a modestly extended version of C. CUDA by Example, written by two senior members of the CUDA software platform team, shows programmers how to employ this new technology. The authors introduce each area of CUDA development through working examples. After a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C, the book details the techniques and trade-offs associated with each key CUDA feature. You’ll discover when to use each CUDA C extension and how to write CUDA software that delivers truly outstanding performance. Major topics covered include Parallel programming Thread cooperation Constant memory and events Texture memory Graphics interoperability Atomics Streams CUDA C on multiple GPUs Advanced atomics Additional CUDA resources All the CUDA software tools you’ll need are freely available for download from NVIDIA. http://developer.nvidia.com/object/cuda-by-example.html
Author: Tor M. Aamodt
Publisher: Synthesis Lectures on Computer
ISBN: 9781681733586
Category : Computers
Languages : en
Pages : 140
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Book Description
Originally developed to support video games, graphics processor units (GPUs) are now increasingly used for general-purpose (non-graphics) applications ranging from machine learning to mining of cryptographic currencies. GPUs can achieve improved performance and efficiency versus central processing units (CPUs) by dedicating a larger fraction of hardware resources to computation. In addition, their general-purpose programmability makes contemporary GPUs appealing to software developers in comparison to domain-specific accelerators. This book provides an introduction to those interested in studying the architecture of GPUs that support general-purpose computing. It collects together information currently only found among a wide range of disparate sources. The authors led development of the GPGPU-Sim simulator widely used in academic research on GPU architectures. The first chapter of this book describes the basic hardware structure of GPUs and provides a brief overview of their history. Chapter 2 provides a summary of GPU programming models relevant to the rest of the book. Chapter 3 explores the architecture of GPU compute cores. Chapter 4 explores the architecture of the GPU memory system. After describing the architecture of existing systems, Chapters \ref{ch03} and \ref{ch04} provide an overview of related research. Chapter 5 summarizes cross-cutting research impacting both the compute core and memory system. This book should provide a valuable resource for those wishing to understand the architecture of graphics processor units (GPUs) used for acceleration of general-purpose applications and to those who want to obtain an introduction to the rapidly growing body of research exploring how to improve the architecture of these GPUs.
Author: Alamelu Sankaranarayanan
Publisher:
ISBN: 9781339626451
Category :
Languages : en
Pages : 130
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Book Description
It is commonplace for graphics processing units or GPUs today to render extremely complex 3D scenes and textures, in real time, both in the traditional and mobile computing spaces. The computational power required to do this makes them a valuable resource to exploit for general purpose computation. In order to map programs originally designed for sequential CPUs onto massively parallel GPU architectures, it would be necessary to justify the transition with huge performance benefits. Over the last couple of years, there have been numerous proposals to improve the performance of GPUs used for general purpose computing (GPGPUs), but without much consideration for energy efficiency.
Author: Preeti Ranjan Panda
Publisher: Springer Science & Business Media
ISBN: 144196388X
Category : Technology & Engineering
Languages : en
Pages : 260
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Book Description
The Information and communication technology (ICT) industry is said to account for 2% of the worldwide carbon emissions – a fraction that continues to grow with the relentless push for more and more sophisticated computing equipment, c- munications infrastructure, and mobile devices. While computers evolved in the directionofhigherandhigherperformanceformostofthelatterhalfofthe20thc- tury, the late 1990’s and early 2000’ssaw a new emergingfundamentalconcern that has begun to shape our day-to-day thinking in system design – power dissipation. As we elaborate in Chapter 1, a variety of factors colluded to raise power-ef?ciency as a ?rst class design concern in the designer’s mind, with profound consequences all over the ?eld: semiconductor process design, circuit design, design automation tools, system and application software, all the way to large data centers. Power-ef?cient System Design originated from a desire to capture and highlight the exciting developments in the rapidly evolving ?eld of power and energy op- mization in electronic and computer based systems. Tremendous progress has been made in the last two decades, and the topic continues to be a fascinating research area. To develop a clearer focus, we have concentrated on the relatively higher level of design abstraction that is loosely called the system level. In addition to the ext- sive coverage of traditional power reduction targets such as CPU and memory, the book is distinguished by detailed coverage of relatively modern power optimization ideas focussing on components such as compilers, operating systems, servers, data centers, and graphics processors.
Author: Sunpyo Hong
Publisher:
ISBN:
Category : Computer architecture
Languages : en
Pages :
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Book Description
The objective of the proposed research is to develop an analytical model that predicts performance and power for many-core architecture and further propose a mechanism, which leverages the analytical model, to enable energy-efficient execution of an application. The key insight of the model is to investigate and quantify a complex relationship that exists between the thread-level parallelism and memory-level parallelism for an application on a given many-core architecture. Two metrics are proposed: memory warp parallelism (MWP), which refers to the number of overlapping memory accesses per core, and computation warp parallelism (CWP), which characterizes an application type. By using these metrics in addition to the architectural and application parameters, the overall application performance is produced. The model uses statically-available parameters such as instruction-mixture information and input-data size, and the prediction accuracy is 13.3% for the GPU-computing benchmarks. Another important aspect of using many-core architecture is reducing peak power and achieving energy savings. By using the proposed integrated power and performance (IPP) framework, the results showed that different optimization points exist for GPU architecture depending on the application type. The work shows that by activating fewer cores, 10.99% of run-time energy consumption can be saved for the bandwidth-limited benchmarks, and a projection of 25.8% energy savings is predicted when power-gating at core level is employed. Finally, the model is shifted to throughput using OpenCL for targeting more variety of processors. First, multiple outputs relating to performance are predicted, including upper-bound and lower-bound values. Second, by using the model parameters, an application can be categorized into a different category, each with its own suggestions for improving performance and energy efficiency. Third, the bandwidth saturation point accuracy is significantly improved by considering independent memory accesses and updating the performance model. Furthermore, a trade-off analysis using architectural and application parameters is straightforward, which provides more insights to improve energy efficiency. In the future, a computer system will contain hundreds of heterogeneous cores. Hence, it is mandatory that a workload gets scheduled to an efficient core or distributed on both types of cores. A preliminary work by using the analytical model to do scheduling between CPU and GPU is demonstrated in the appendix. Since profiling phase is not required, the kernel code can be transformed to run more efficiently on the specific architecture. Another extension of the work regarding the relationship between the speed-up and energy efficiency is mathematically derived. Finally, future research ideas are presented regarding the usage of the model for programmer, compiler, and runtime for future heterogeneous systems.
Author: Raphael Couturier
Publisher: CRC Press
ISBN: 1466571624
Category : Mathematics
Languages : en
Pages : 500
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Book Description
Many of today’s complex scientific applications now require a vast amount of computational power. General purpose graphics processing units (GPGPUs) enable researchers in a variety of fields to benefit from the computational power of all the cores available inside graphics cards. Understand the Benefits of Using GPUs for Many Scientific Applications Designing Scientific Applications on GPUs shows you how to use GPUs for applications in diverse scientific fields, from physics and mathematics to computer science. The book explains the methods necessary for designing or porting your scientific application on GPUs. It will improve your knowledge about image processing, numerical applications, methodology to design efficient applications, optimization methods, and much more. Everything You Need to Design/Port Your Scientific Application on GPUs The first part of the book introduces the GPUs and Nvidia’s CUDA programming model, currently the most widespread environment for designing GPU applications. The second part focuses on significant image processing applications on GPUs. The third part presents general methodologies for software development on GPUs and the fourth part describes the use of GPUs for addressing several optimization problems. The fifth part covers many numerical applications, including obstacle problems, fluid simulation, and atomic physics models. The last part illustrates agent-based simulations, pseudorandom number generation, and the solution of large sparse linear systems for integer factorization. Some of the codes presented in the book are available online.
