{"product_id":"electronic-structure-calculations-on-graphics-processing-units-9781118661789","title":"Electronic Structure Calculations on Graphics","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003ci\u003eElectronic Structure Calculations on Graphics Processing Units: From Quantum Chemistry to Condensed Matter Physics\u003c\/i\u003e provides an overview of computing on graphics processing units (GPUs), a brief introduction to GPU programming, and the latest examples of code developments and applications for the most widely used electronic structure methods.\u003c\/p\u003e \u003cp\u003eThe book covers all commonly used basis sets including localized Gaussian and Slater type basis functions, plane waves, wavelets and real-space grid-based approaches. \u003cbr\u003eThe chapters expose details on the calculation of two-electron integrals, exchange-correlation quadrature, Fock matrix formation, solution of the self-consistent field equations, calculation of nuclear gradients to obtain forces, and methods to treat excited states within DFT. Other chapters focus on semiempirical and correlated wave function methods including density fitted second order Møller-Plesset perturbation theory and both iterative and perturbative sing\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eList of Contributors xiii\u003c\/p\u003e \u003cp\u003ePreface xvii\u003c\/p\u003e \u003cp\u003eAcknowledgments xix\u003c\/p\u003e \u003cp\u003eGlossary xxi\u003c\/p\u003e \u003cp\u003eAbbreviations xxv\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1. Why Graphics Processing Units 1”\u003cbr\u003e \u003c\/b\u003e\u003ci\u003ePerri Needham, Andreas W. Götz and Ross C. Walker\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 A Historical Perspective of Parallel Computing 1\u003c\/p\u003e \u003cp\u003e1.2 The Rise of the GPU 5\u003c\/p\u003e \u003cp\u003e1.3 Parallel Computing on Central Processing Units 7\u003c\/p\u003e \u003cp\u003e1.4 Parallel Computing on Graphics Processing Units 12\u003c\/p\u003e \u003cp\u003e1.5 GPU-Accelerated Applications 15\u003c\/p\u003e \u003cp\u003eReferences 19\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2. GPUs: Hardware to Software 23\u003cbr\u003e \u003c\/b\u003e\u003ci\u003ePerri Needham, Andreas W. Götz and Ross C. Walker\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Basic GPU Terminology 24\u003c\/p\u003e \u003cp\u003e2.2 Architecture of GPUs 24\u003c\/p\u003e \u003cp\u003e2.3 CUDA Programming Model 26\u003c\/p\u003e \u003cp\u003e2.4 Programming and Optimization Concepts 30\u003c\/p\u003e \u003cp\u003e2.5 Software Libraries for GPUs 34\u003c\/p\u003e \u003cp\u003e2.6 Special Features of CUDA-Enabled GPUs 35\u003c\/p\u003e \u003cp\u003eReferences 36\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3. Overview of Electronic Structure Methods 39\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAndreas W. Götz\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 39\u003c\/p\u003e \u003cp\u003e3.2 Hartree–Fock Theory 42\u003c\/p\u003e \u003cp\u003e3.3 Density Functional Theory 46\u003c\/p\u003e \u003cp\u003e3.4 Basis Sets 49\u003c\/p\u003e \u003cp\u003e3.5 Semiempirical Methods 53\u003c\/p\u003e \u003cp\u003e3.6 Density Functional Tight Binding 56\u003c\/p\u003e \u003cp\u003e3.7 Wave Function-Based Electron Correlation Methods 57\u003c\/p\u003e \u003cp\u003eAcknowledgments 60\u003c\/p\u003e \u003cp\u003eReferences 61\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4. Gaussian Basis Set Hartree–Fock, Density Functional Theory, and Beyond on GPUs 67\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eNathan Luehr, Aaron Sisto and Todd J. Martínez\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Quantum Chemistry Review 68\u003c\/p\u003e \u003cp\u003e4.2 Hardware and CUDA Overview 72\u003c\/p\u003e \u003cp\u003e4.3 GPU ERI Evaluation 73\u003c\/p\u003e \u003cp\u003e4.4 Integral-Direct Fock Construction on GPUs 78\u003c\/p\u003e \u003cp\u003e4.5 Precision Considerations 88\u003c\/p\u003e \u003cp\u003e4.6 Post-SCF Methods 91\u003c\/p\u003e \u003cp\u003e4.7 Example Calculations 93\u003c\/p\u003e \u003cp\u003e4.8 Conclusions and Outlook 97\u003c\/p\u003e \u003cp\u003eReferences 98\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5. GPU Acceleration for Density Functional Theory with Slater-Type Orbitals 101\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eHans van Schoot and Lucas Visscher\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Background 101\u003c\/p\u003e \u003cp\u003e5.2 Theory and CPU Implementation 102\u003c\/p\u003e \u003cp\u003e5.3 GPU Implementation 105\u003c\/p\u003e \u003cp\u003e5.4 Conclusion 112\u003c\/p\u003e \u003cp\u003eReferences 113\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6. Wavelet-Based Density Functional Theory on Massively Parallel Hybrid Architectures 115\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eLuigi Genovese, Brice Videau, Damien Caliste, Jean-François Méhaut, Stefan Goedecker and Thierry Deutsch\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introductory Remarks on Wavelet Basis Sets for Density Functional Theory Implementations 115\u003c\/p\u003e \u003cp\u003e6.2 Operators in Wavelet Basis Sets 117\u003c\/p\u003e \u003cp\u003e6.3 Parallelization 123\u003c\/p\u003e \u003cp\u003e6.4 GPU Architecture 124\u003c\/p\u003e \u003cp\u003e6.5 Conclusions and Outlook 132\u003c\/p\u003e \u003cp\u003eReferences 133\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7. Plane-Wave Density Functional Theory 135\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMaxwell Hutchinson, Paul Fleurat-Lessard, Ani Anciaux-Sedrakian, Dusan Stosic, Jeroen Bédorf and Sarah Tariq\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 135\u003c\/p\u003e \u003cp\u003e7.2 Theoretical Background 136\u003c\/p\u003e \u003cp\u003e7.3 Implementation 143\u003c\/p\u003e \u003cp\u003e7.4 Optimizations 148\u003c\/p\u003e \u003cp\u003e7.5 Performance Examples 151\u003c\/p\u003e \u003cp\u003e7.6 Exact Exchange with Plane Waves 159\u003c\/p\u003e \u003cp\u003e7.7 Summary and Outlook 165\u003c\/p\u003e \u003cp\u003eAcknowledgments 165\u003c\/p\u003e \u003cp\u003eReferences 165\u003c\/p\u003e \u003cp\u003eAppendix A: Definitions and Conventions 168\u003c\/p\u003e \u003cp\u003eAppendix B: Example Kernels 168\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8. GPU-Accelerated Sparse Matrix–Matrix Multiplication for Linear Scaling Density Functional Theory 173\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eOle Schütt, Peter Messmer, Jürg Hutter and Joost VandeVondele\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 173\u003c\/p\u003e \u003cp\u003e8.2 Software Architecture for GPU-Acceleration 177\u003c\/p\u003e \u003cp\u003e8.3 Maximizing Asynchronous Progress 180\u003c\/p\u003e \u003cp\u003e8.4 Libcusmm: GPU Accelerated Small Matrix Multiplications 183\u003c\/p\u003e \u003cp\u003e8.5 Benchmarks and Conclusions 186\u003c\/p\u003e \u003cp\u003eAcknowledgments 189\u003c\/p\u003e \u003cp\u003eReferences 189\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9. Grid-Based Projector-Augmented Wave Method 191\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eSamuli Hakala, Jussi Enkovaara, Ville Havu, Jun Yan, Lin Li, Chris O’Grady\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eand Risto M. Nieminen\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 191\u003c\/p\u003e \u003cp\u003e9.2 General Overview 193\u003c\/p\u003e \u003cp\u003e9.3 Using GPUs in Ground-State Calculations 196\u003c\/p\u003e \u003cp\u003e9.4 Time-Dependent Density Functional Theory 202\u003c\/p\u003e \u003cp\u003e9.5 Random Phase Approximation for the Correlation Energy 203\u003c\/p\u003e \u003cp\u003e9.6 Summary and Outlook 207\u003c\/p\u003e \u003cp\u003eAcknowledgments 208\u003c\/p\u003e \u003cp\u003eReferences 208\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10. Application of Graphics Processing Units to Accelerate Real-Space Density Functional Theory and Time-Dependent Density Functional Theory Calculations 211\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eXavier Andrade and Alán Aspuru-Guzik\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 212\u003c\/p\u003e \u003cp\u003e10.2 The Real-Space Representation 213\u003c\/p\u003e \u003cp\u003e10.3 Numerical Aspects of the Real-Space Approach 214\u003c\/p\u003e \u003cp\u003e10.4 General GPU Optimization Strategy 216\u003c\/p\u003e \u003cp\u003e10.5 Kohn–Sham Hamiltonian 217\u003c\/p\u003e \u003cp\u003e10.6 Orthogonalization and Subspace Diagonalization 221\u003c\/p\u003e \u003cp\u003e10.7 Exponentiation 222\u003c\/p\u003e \u003cp\u003e10.8 The Hartree Potential 223\u003c\/p\u003e \u003cp\u003e10.9 Other Operations 224\u003c\/p\u003e \u003cp\u003e10.10 Numerical Performance 225\u003c\/p\u003e \u003cp\u003e10.11 Conclusions 228\u003c\/p\u003e \u003cp\u003e10.12 Computational Methods 228\u003c\/p\u003e \u003cp\u003eAcknowledgments 229\u003c\/p\u003e \u003cp\u003eReferences 229\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11. Semiempirical Quantum Chemistry 239\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eXin Wu, Axel Koslowski and Walter Thiel\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 239\u003c\/p\u003e \u003cp\u003e11.2 Overview of Semiempirical Methods 240\u003c\/p\u003e \u003cp\u003e11.3 Computational Bottlenecks 241\u003c\/p\u003e \u003cp\u003e11.4 Profile-Guided Optimization for the Hybrid Platform 244\u003c\/p\u003e \u003cp\u003e11.5 Performance 249\u003c\/p\u003e \u003cp\u003e11.6 Applications 251\u003c\/p\u003e \u003cp\u003e11.7 Conclusion 252\u003c\/p\u003e \u003cp\u003eAcknowledgement 253\u003c\/p\u003e \u003cp\u003eReferences 253\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12. GPU Acceleration of Second-Order Møller–Plesset Perturbation Theory with Resolution of Identity 259\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRoberto Olivares-Amaya, Adrian Jinich, Mark A. Watson and Alán Aspuru-Guzik\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Møller–Plesset Perturbation Theory with Resolution of Identity Approximation (RI-MP2) 259\u003c\/p\u003e \u003cp\u003e12.2 A Mixed-Precision Matrix Multiplication Library 263\u003c\/p\u003e \u003cp\u003e12.3 Performance of Accelerated RI-MP2 266\u003c\/p\u003e \u003cp\u003e12.4 Example Applications 270\u003c\/p\u003e \u003cp\u003e12.5 Conclusions 273\u003c\/p\u003e \u003cp\u003eReferences 273\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13. Iterative Coupled-Cluster Methods on Graphics Processing Units 279\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eA. Eugene DePrince III, Jeff R. Hammond and C. David Sherrill\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 279\u003c\/p\u003e \u003cp\u003e13.2 Related Work 280\u003c\/p\u003e \u003cp\u003e13.3 Theory 281\u003c\/p\u003e \u003cp\u003e13.4 Algorithm Details 284\u003c\/p\u003e \u003cp\u003e13.5 Computational Details 287\u003c\/p\u003e \u003cp\u003e13.6 Results 290\u003c\/p\u003e \u003cp\u003e13.7 Conclusions 295\u003c\/p\u003e \u003cp\u003eAcknowledgments 296\u003c\/p\u003e \u003cp\u003eReferences 296\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14. Perturbative Coupled-Cluster Methods on Graphics Processing Units: Single- and Multi-Reference Formulations 301\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eWenjing Ma, Kiran Bhaskaran-Nair, Oreste Villa, Edoardo Aprà, Antonino Tumeo, Sriram Krishnamoorthy and Karol Kowalski\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 302\u003c\/p\u003e \u003cp\u003e14.2 Overview of Electronic Structure Methods 303\u003c\/p\u003e \u003cp\u003e14.3 NWChem Software Architecture 308\u003c\/p\u003e \u003cp\u003e14.4 GPU Implementation 309\u003c\/p\u003e \u003cp\u003e14.5 Performance 315\u003c\/p\u003e \u003cp\u003e14.6 Outlook 319\u003c\/p\u003e \u003cp\u003eAcknowledgments 320\u003c\/p\u003e \u003cp\u003eReferences 320\u003c\/p\u003e \u003cp\u003eIndex 327\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49528834589015,"sku":"9781118661789","price":125.95,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781118661789.jpg?v=1731873205","url":"https:\/\/bookcurl.com\/products\/electronic-structure-calculations-on-graphics-processing-units-9781118661789","provider":"Book Curl","version":"1.0","type":"link"}