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1. The Microarchitectural Schism: Latency versus Throughput The trajectory of modern computing capabilities is defined not by a singular linear progression of speed, but by a fundamental bifurcation in architectural Read More …
The Imperative for Specialization: From General-Purpose GPUs to AI-Centric Accelerators The trajectory of modern artificial intelligence (AI) is inextricably linked to the evolution of the hardware that powers it. For Read More …
The Imperative for Domain-Specific Acceleration The landscape of computing has been defined for decades by the relentless progress of general-purpose processors. However, the dawn of the deep learning era in Read More …
Executive Summary The selection of hardware for training deep learning models has evolved into a critical strategic decision, with Graphics Processing Unit (GPU) and Tensor Processing Unit (TPU) representing two Read More …