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Related lectures (32)

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Accelerator-centric OS Architecture

By the instructor Mark Silberstein explores accelerator-centric OS architecture and the role of CPUs in modern computers.

Fast Interconnects: Scalable Co-processing with GPUs

Explores the use of fast interconnects for scalable co-processing with GPUs in databases, emphasizing the importance of overcoming the transfer bottleneck and reevaluating assumptions for performance improvements.

GPUs: Multithreading and Architecture

Explores GPUs' architecture, multithreading, and their role in machine learning, discussing limitations and future trends.

GPUs: Architecture and Programming

Explores GPU architecture, multithreading, SIMD processors, and CUDA programming for parallel computing.

GPU Introduction: Performance and Programming

Explores the motivation and advantages of using GPUs for computation, focusing on their performance and programming through CUDA.

Accelerated Data Management Systems

Explores accelerated data management systems through real-time specialization on heterogeneous hardware and GPU accessing fresh data from CPU memory.

GPUs: Introduction to CUDA

Introduces the basics of GPUs, CUDA programming, and thread synchronization for parallel computing applications.

Efficient GPU Join Optimization

Covers efficient GPU-accelerated join optimization for complex queries, focusing on improving optimization times and heuristic plan quality.

Translations and Homotheties

Covers translations, homotheties, and their geometric properties, including reversibility and composition.

Linear Algebra: Applications and Definitions

Covers the definition of applications, image of elements, and direct and reciprocal images.