Heterogeneous Computing with OpenCL, Second Edition teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs) such as AMD Fusion technology. It is the first textbook that presents OpenCL programming appropriate for the classroom and is intended to support a parallel programming course. Students will come away from this text with hands-on experience and significant knowledge of the syntax and use of OpenCL to address a range of fundamental parallel algorithms.
Designed to work on multiple platforms and with wide industry support, OpenCL will help you more effectively program for a heterogeneous future. Written by leaders in the parallel computing and OpenCL communities, Heterogeneous Computing with OpenCL explores memory spaces, optimization techniques, graphics interoperability, extensions, and debugging and profiling. It includes detailed examples throughout, plus additional online exercises and other supporting materials that can be downloaded at http://www.heterogeneouscompute.org/?page_id=7
This book will appeal to software engineers, programmers, hardware engineers, and students/advanced students.
"synopsis" may belong to another edition of this title.
Heterogeneous Computing with OpenCL teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and fully-integrated Accelerated Processing Units (APUs) such as AMD Fusion technology. Designed to work on multiple platforms and with wide industry support, OpenCL will help you more effectively program for a heterogeneous future.
Written by leaders in the parallel computing and OpenCL communities, this book will give you hands-on OpenCL experience to address a range of fundamental parallel algorithms. The authors explore memory spaces, optimization techniques, graphics interoperability, extensions, and debugging and profiling. Intended to support a parallel programming course, Heterogeneous Computing with OpenCL includes detailed examples throughout, plus additional online exercises and other supporting materials.
Features
Dr. Kaeli has co-authored more than 200 critically reviewed publications. His research spans a range of areas including microarchitecture to back-end compilers and software engineering. He leads a number of research projects in the area of GPU Computing. He presently serves as the Chair of the IEEE Technical Committee on Computer Architecture. Dr. Kaeli is an IEEE Fellow and a member of the ACM.
Perhaad Mistry works in AMD’s developer tools group at the Boston Design Center focusing on developing debugging and performance profiling tools for heterogeneous architectures. He is presently focused on debugger architectures for upcoming platforms shared memory and discrete Graphics Processing Unit (GPU) platforms. Perhaad has been working on GPU architectures and parallel programming since CUDA 0.8 in 2007. He has enjoyed implementing medical imaging algorithms for GPGPU platforms and architecture aware data structures for surgical simulators. Perhaad's present work focuses on the design of debuggers and architectural support for performance analysis for the next generation of applications that will target GPU platforms.
Perhaad graduated after 7 years with a PhD from Northeastern University in Electrical and Computer Engineering and was advised by Dr. David Kaeli who the leads Northeastern University Computer Architecture Research Laboratory (NUCAR). Even after graduating, Perhaad is still a member of NUCAR and is advising on research projects on performance analysis of parallel architectures. He received a BS in Electronics Engineering from University of Mumbai and an MS in Computer Engineering from Northeastern University in Boston. He is presently based in Boston.
Dana Schaa received a BS in Computer Engineering from Cal Poly, San Luis Obispo, and an MS and PhD in Electrical and Computer Engineering from Northeastern University. He works on GPU architecture modeling at AMD, and has interests and expertise that include memory systems, microarchitecture, performance analysis, and general purpose computing on GPUs. His background includes the development OpenCL-based medical imaging applications ranging from real-time visualization of 3D ultrasound to CT image reconstruction in heterogeneous environments. Dana married his wonderful wife Jenny in 2010, and they live together in San Jose with their charming cats.
"About this title" may belong to another edition of this title.
Shipping:
FREE
Within U.S.A.
Book Description Condition: Brand New. New.SoftCover International edition. Different ISBN and Cover image but contents are same as US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Seller Inventory # ABEOCT23-198304
Book Description Condition: New. Brand New Paperback International Edition.We Ship to PO BOX Address also. EXPEDITED shipping option also available for faster delivery.This item may ship from the US or other locations in India depending on your location and availability. Seller Inventory # ABTR-3679
Book Description Paperback. Condition: new. Brand New Copy. Seller Inventory # BBB_new0124058949
Book Description Paperback. Condition: new. New. Fast Shipping and good customer service. Seller Inventory # Holz_New_0124058949
Book Description Paperback. Condition: new. New Copy. Customer Service Guaranteed. Seller Inventory # think0124058949
Book Description Paperback. Condition: new. New. Seller Inventory # Wizard0124058949
Book Description Paperback. Condition: New. Seller Inventory # 6666-ELS-9780124058941
Book Description Condition: new. Questo è un articolo print on demand. Seller Inventory # 58e15c53cd25e5c700c07072f2b6be1c
Book Description Paperback. Condition: Brand New. 2nd revised edition. 304 pages. 9.10x0.70x7.50 inches. In Stock. Seller Inventory # __0124058949
Book Description Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days. Teaches OpenCL and parallel programming for complex systems that may include a variety of device architectures: multi-core CPUs, GPUs, and integrated Accelerated Processing Units (APUs) such as AMD Fusion technology. This book explores memory spaces, optimization techniques, graphics interoperability, extensions, and debugging and profiling. Seller Inventory # B9780124058941