LEADER 05589nam 22007453u 450 001 9910966759003321 005 20240405033429.0 010 $a9781118739273 010 $a1118739272 035 $a(CKB)2550000001349255 035 $a(EBL)1776323 035 $a(SSID)ssj0001414088 035 $a(PQKBManifestationID)11777378 035 $a(PQKBTitleCode)TC0001414088 035 $a(PQKBWorkID)11431679 035 $a(PQKB)11207272 035 $a(MiAaPQ)EBC1776323 035 $a(Perlego)2766495 035 $a(EXLCZ)992550000001349255 100 $a20140908d2014|||| u|| | 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aProfessional CUDA C Programming 205 $a1st ed. 210 $aHoboken $cWiley$d2014 215 $a1 online resource (527 p.) 300 $aDescription based upon print version of record. 311 08$a9781118739327 311 08$a1118739329 311 08$a9781322094908 311 08$a132209490X 327 $aCover; Title Page; Copyright; Contents; Chapter 1 Heterogeneous Parallel Computing with CUDA; Parallel Computing; Sequential and Parallel Programming; Parallelism; Computer Architecture; Heterogeneous Computing; Heterogeneous Architecture; Paradigm of Heterogeneous Computing; CUDA: A Platform for Heterogeneous Computing; Hello World from GPU; Is CUDA C Programming Difficult?; Summary; Chapter 2 CUDA Programming Model; Introducing the CUDA Programming Model; CUDA Programming Structure; Managing Memory; Organizing Threads; Launching a CUDA Kernel; Writing Your Kernel; Verifying Your Kernel 327 $aHandling ErrorsCompiling and Executing; Timing Your Kernel; Timing with CPU Timer; Timing with nvprof; Organizing Parallel Threads; Indexing Matrices with Blocks and Threads; Summing Matrices with a 2D Grid and 2D Blocks; Summing Matrices with a 1D Grid and 1D Blocks; Summing Matrices with a 2D Grid and 1D Blocks; Managing Devices; Using the Runtime API to Query GPU Information; Determining the Best GPU; Using nvidia-smi to Query GPU Information; Setting Devices at Runtime; Summary; Chapter 3 CUDA Execution Model; Introducing the CUDA Execution Model; GPU Architecture Overview 327 $aThe Fermi ArchitectureThe Kepler Architecture; Profile-Driven Optimization; Understanding the Nature of Warp Execution; Warps and Thread Blocks; Warp Divergence; Resource Partitioning; Latency Hiding; Occupancy; Synchronization; Scalability; Exposing Parallelism; Checking Active Warps with nvprof; Checking Memory Operations with nvprof; Exposing More Parallelism; Avoiding Branch Divergence; The Parallel Reduction Problem; Divergence in Parallel Reduction; Improving Divergence in Parallel Reduction; Reducing with Interleaved Pairs; Unrolling Loops; Reducing with Unrolling 327 $aReducing with Unrolled WarpsReducing with Complete Unrolling; Reducing with Template Functions; Dynamic Parallelism; Nested Execution; Nested Hello World on the GPU; Nested Reduction; Summary; Chapter 4 Global Memory; Introducing the CUDA Memory Model; Benefits of a Memory Hierarchy; CUDA Memory Model; Memory Management; Memory Allocation and Deallocation; Memory Transfer; Pinned Memory; Zero-Copy Memory; Unified Virtual Addressing; Unified Memory; Memory Access Patterns; Aligned and Coalesced Access; Global Memory Reads; Global Memory Writes; Array of Structures versus Structure of Arrays 327 $aPerformance TuningWhat Bandwidth Can a Kernel Achieve?; Memory Bandwidth; Matrix Transpose Problem; Matrix Addition with Unified Memory; Summary; Chapter 5 Shared Memory and Constant Memory; Introducing CUDA Shared Memory; Shared Memory; Shared Memory Allocation; Shared Memory Banks and Access Mode; Configuring the Amount of Shared Memory; Synchronization; Checking the Data Layout of Shared Memory; Square Shared Memory; Rectangular Shared Memory; Reducing Global Memory Access; Parallel Reduction with Shared Memory; Parallel Reduction with Unrolling 327 $aParallel Reduction with Dynamic Shared Memory 330 $a Break into the powerful world of parallel GPU programming with this down-to-earth, practical guide Designed for professionals across multiple industrial sectors, Professional CUDA C Programming presents CUDA -- a parallel computing platform and programming model designed to ease the development of GPU programming -- fundamentals in an easy-to-follow format, and teaches readers how to think in parallel and implement parallel algorithms on GPUs. Each chapter covers a specific topic, and includes workable examples that demonstrate the development process, allowing readers to explore both the " 606 $aComputer architecture 606 $aMultiprocessors 606 $aParallel processing (Electronic computers) 606 $aParallel programming (Computer science) 606 $aEngineering & Applied Sciences$2HILCC 606 $aComputer Science$2HILCC 615 4$aComputer architecture. 615 4$aMultiprocessors. 615 4$aParallel processing (Electronic computers). 615 4$aParallel programming (Computer science). 615 7$aEngineering & Applied Sciences 615 7$aComputer Science 676 $a004.35 676 $a004/.35 700 $aCheng$b John$01172563 701 $aGrossman$b Max$01172564 701 $aMcKercher$b Ty$01172565 801 0$bAU-PeEL 801 1$bAU-PeEL 801 2$bAU-PeEL 906 $aBOOK 912 $a9910966759003321 996 $aProfessional CUDA C Programming$92727553 997 $aUNINA LEADER 02693nam 2200589Ia 450 001 9910961800903321 005 20251117065202.0 010 $a1-907343-03-2 035 $a(CKB)2670000000079619 035 $a(EBL)3007761 035 $a(SSID)ssj0000471179 035 $a(PQKBManifestationID)11297790 035 $a(PQKBTitleCode)TC0000471179 035 $a(PQKBWorkID)10417266 035 $a(PQKB)10710296 035 $a(OCoLC)715163813 035 $a(MiAaPQ)EBC3007761 035 $a(Au-PeEL)EBL3007761 035 $a(CaPaEBR)ebr10451057 035 $a(OCoLC)708570906 035 $a(BIP)35545683 035 $a(BIP)27691635 035 $a(EXLCZ)992670000000079619 100 $a20100218d2009 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMass growth of large PbWO4 single crystals for particle detection in high-energy experiments at CERN /$fA.N. Annenkov, Yu.S. Kuz'minov 210 $aCambridge, UK $cCambridge International Science Publishing$d2009 215 $a1 online resource (118 p.) 300 $aDescription based upon print version of record. 311 08$a1-904602-88-6 320 $aIncludes bibliographical references (p. 102-106) and index. 327 $a""Contents""; ""Preface""; ""Introduction""; ""1. Application of crystalline scintillators in high-energy physics""; ""2. Control of defect formation in lead tungstate crystals""; ""3. Technology for mass production of lead tungstate single crystals""; ""4. A quality control system in mass production of lead tungstate crystals""; ""Conclusions""; ""References""; ""Index"" 330 $a A unique book describing the develoment of systems for mass production of lead tungstate crystals for high-energy physics experiments at CERN, Geneva. The properties of the crystals, characteristics of growth equipment and, in particular, quality control of described are described in detail. The book will be of considerable interest to crystal growth experts and scientists working in the area of high-energy physics. 606 $aCrystal growth 606 $aInorganic scintillators 606 $aParticles (Nuclear physics) 615 0$aCrystal growth. 615 0$aInorganic scintillators. 615 0$aParticles (Nuclear physics) 700 $aAnnenkov$b A. N$01869717 701 $aKuz'minov$b I?U. S$g(I?Urii? Sergeevich)$0872053 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910961800903321 996 $aMass growth of large PbWO4 single crystals for particle detection in high-energy experiments at CERN$94477944 997 $aUNINA