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• Digital Design & Computer Architecture - L... This lecture provides a technical overview of Graphics Processing Units (GPUs), characterizing them as simd engines that utilize fine-grained multi-threading to maximize hardware efficiency. The text distinguishes between the programming model, where developers write code for individual threads, and the execution model, where the hardware organizes these threads into warps for parallel processing. To address performance bottlenecks like branch divergence and memory latency, the source explores architectural solutions such as dynamic warp formation and specialized memory hierarchies. Furthermore, the discussion details the evolution of GPU components, specifically highlighting how tensor cores and systolic arrays are integrated to accelerate modern machine learning workloads. Ultimately, the material emphasizes that gpus achieve high throughput by hiding long-latency operations through the constant interleaving of concurrent instruction streams. #gpu #graphics #computerscience #hardware