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CS 348K: Visual Computing Systems

Visual computing tasks such as computational photography, image/video understanding, and real-time 3D graphics are key responsibilities of modern computer systems ranging from sensor-rich smart phones, autonomous robots, and large data centers. These workloads demand exceptional system efficiency and this course examines the key ideas, techniques, and challenges associated with the design of parallel, heterogeneous systems that execute and accelerate visual computing applications. This course is intended for graduate and advanced undergraduate-level students interested in architecting efficient graphics, image processing, and computer vision systems (both new hardware architectures and domain-optimized programming frameworks) and for students in graphics, vision, and ML that seek to understand throughput computing concepts so they can develop scalable algorithms for these platforms. Students will perform daily research paper readings, complete simple programming assignments, and compete a self-selected term project. Prerequisites: CS 107 or equivalent. Highly recommended: Parallel Computing (CS149) or Computer Architecture (EE 282). Students will benefit from some background in deep learning (CS 230, CS 231N), computer vision (CS 231A), digital image processing (CS 232) or computer graphics (CS248).
Terms: Spr | Units: 3-4 | Grading: Letter or Credit/No Credit

EE 282: Computer Systems Architecture

Course focuses on how to build modern computing systems, namely notebooks, smartphones, and data centers, covering primarily their hardware architecture and certain system software aspects. For each system class, we cover the system architecture, processor technology, advanced memory hierarchy and I/O organization, power and energy management, and reliability. We will also cover topics such as interactions with system software, virtualization, solid state storage, and security. The programming assignments allow students to explore performance/energy tradeoffs when using heterogeneous hardware resources on smartphone devices. Prerequisite: EE108B. Recommended: CS 140.
Terms: Win | Units: 3 | Grading: Letter or Credit/No Credit
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