“…Major topics covered include: Natural effects Lighting and shadows Materials Image processing Performance and practicalities Beyond triangles Contributors are from the following universities and corporations: Alias Systems Brown University Croteam Cyan Worlds Hochschule Bremen Industrial Light & Magic iXBT.com Monolith Productions New York University Novarama NVIDIA Paralelo Computacao Piranha Bytes Pixar Animation Studios Siemens Medical Solutions Softimage Co. …”

“…With fresh offerings from Arduino and Raspberry Pi and powerhouse boards like DFRobot's LattePanda Sigma and Nvidia's Jetson Orin Nano, it's easier than ever to put epic computing power for your next project in the palm of your hand.In this issue of Make: we track new trends in microcontrollers and single board computers, and show you the ones we're most excited about. …”

“…As a leader in visual computing technologies, NVIDIA has become a partner for many organizations taking the plunge into AI. …”

“…As you progress, you’ll harness the power of AI platforms to streamline the deep learning life cycle and leverage Python libraries and frameworks such as PyTorch, ONNX, Catalyst, MLFlow, Captum, Nvidia Triton, Prometheus, and Grafana to execute efficient deep learning architectures, optimize model performance, and streamline the deployment processes. …”

“…We've packaged the invaluable insights and techniques shared by bestselling AI authors, innovators, and practitioners from Meta, Microsoft, Deloitte, JPMorgan, NVIDIA, Salesforce, and more. These talks and tech sessions provide unique perspectives on realizing generative AI's immense potential. …”

“…Already implemented by Apple, AMD, Intel, IBM, NVIDIA, and other leaders, OpenCL has outstanding potential for PCs, servers, handheld/embedded devices, high performance computing, and even cloud systems. …”

“…-Nicolas Pinto, Research Scientist at Harvard & MIT, NVIDIA Fellow 2009-2010 Graphics processing units (GPUs) can do much more than render graphics. …”

“…This year brings powerful new releases from Adafruit, Arduino, BeagleBoard, Google, Nvidia, Raspberry Pi, Teensy, and more. We’ve assembled the technical data for new boards and returning favorites (listing over 50% more than our previous guide!)…”

“….), and the leaders of AI product development from many of the world's top technology companies (IBM, Intel, Google, Amazon, Facebook, NVIDIA, Microsoft, Salesforce, SAP, etc.). This video compilation is a record of the 90+ presentations made by this extraordinary group. …”

“…Discover what overfitting means and how to recognize it in deep learning models Understand how to sample your data to reduce the likelihood of overfitting Learn about regularization and its use as a remedy for overfitting Laura Graesser is assisting in NVIDIA's autonomous driving project. Previously with The Boston Consulting Group, Laura is a graduate student at New York University, where she's working toward a master’s degree in computer science and machine learning. …”

“…Simon demonstrates how you can save up to $5,000 a month in cloud processing and storage costs while delivering accurate predictions that can transform outcomes, using well-established architectural pillars, such as the distributed actor model, to process voluminous real-time data at the edge, along with the rich commons of open source analytics and learning tools like Flink and Spark, on nothing more than a $200 device such as an NVIDIA Jetson. The key insight is to use streaming data to build a digital twin model on the fly at the edge, avoiding a ton of complexity and infrastructure costs. …”

Tabla de Contenidos: “…CUDA and Amdahl's LawData and Task Parallelism; Hybrid Execution: Using Both CPU and GPU Resources; Regression Testing and Accuracy; Silent Errors; Introduction to Debugging; UNIX Debugging; NVIDIA's cuda-gdb Debugger; The CUDA Memory Checker; Use cuda-gdb with the UNIX ddd Interface; Windows Debugging with Parallel Nsight; Summary; 2 CUDA for Machine Learning and Optimization; Modeling and Simulation; Fitting Parameterized Models; Nelder-Mead Method; Levenberg-Marquardt Method; Algorithmic Speedups; Machine Learning and Neural Networks; XOR: An Important Nonlinear Machine-Learning Problem…”

Tabla de Contenidos: “…Appendix A: Terms and DefinitionsAppendix B: Trading Examples; Example 1: Consolidation Breakout from Range; Example 2: Consolidation Breakdown-Going Short; Example 3: Building a Trade; Appendix C: Spreadsheet Examples; Appendix D: Supporting Data for Nvidia Example in Chapter 4; About the Author; Index…”

Tabla de Contenidos: “…GPU Debugging and Profiling with NVIDIA Parallel NsightChapter 22. FBX Games Development Tools; About the Contributors; Color Insert; Back cover…”

“…The book also helps users get the most from the latest NVIDIA and AMD GPU plus multicore CPU architectures (and soon for Intel® Xeon PhiTM as well). …”

“…Two IBM POWER9 processor-based single-chip module (SCM) devices that provide high performance with 24, 32, or 40 fully activated cores and a maximum 2 TB of memory. Up to six NVIDIA T4 graphics processing unit (GPU) accelerators. …”

Tabla de Contenidos: “…Develop Applications; 34. Install Nvidia 3D Drivers; Get the Nvidia Installer; 35. Point-and-Klik to Install Applications; 36. …”

Tabla de Contenidos: “…SHADER TOOLS & RESOURCES; RenderMonkey; NVIDIA Effects Browser; NVIDIA Shader Debugger; Shader Studio; ColorSpace Tool; Resources; CHAPTER 7. …”

“…This book documents the HPC clustering solution with InfiniBand on IBM Power SystemsTM AC922 8335-GTH and 8335-GTX servers with NVIDIA Tesla V100 SXM2 graphics processing units (GPUs) with NVLink, software components, and the IBM SpectrumTM Scale parallel file system. …”