The Computing Hardware and Emerging Architectures thread focuses on the physical realization of computing systems—the inner workings that compute, remember, learn, and communicate results. It deals with the challenges of making computing devices respond quickly and reliably, while being energy efficient, for example, to maximize battery life or to create environmentally sustainable data centers. It explores computing architectures that integrate millions of processing elements working in synchrony to accelerate machine learning, medical image analysis, climate modeling, and other computationally intense applications. This thread also explores new computing technologies inspired by biology and quantum physics such as neuromorphic and quantum computing.

Sample of related career paths:

• Computer chip and digital system design, VLSI engineer (Intel, Qualcomm, AMD, IBM, Apple, Texas Instruments, Samsung, Nvidia etc.)
• Computer architecture and parallel processing (ARM, Advanced Micro Devices, Intel, etc.)
• Smart phones and mobile platforms (Qualcomm, Apple, Samsung, etc.)
• Cloud and edge computing (Google, Amazon AWS, Microsoft Azure, Dropbox, Oracle, Ericsson, ARM, IBM, Cisco, etc.)
• Emerging computing technologies: quantum, neuromorphic, etc. (IBM, Intel, Google, HP, Samsung, and several smaller companies)
• Memory systems (Rambus, Avalanche Technology, MoSys, Netlist, etc.)
• Low power, reconfigurable systems/FPGAs (Altera/Intel, Xilinx, Lattice Semiconductor, etc.)
• Embedded systems (ARM, Ericsson, Texas Instruments, etc.)
• Hardware acceleration for machine learning, CGI, augmented/virtual reality (Nvidia, Google, Intel, etc.)
• Cybersecurity (CISCO, Broadcom, Fortinet, etc.)
• High performance computing (National laboratories, AMD, Cray, Intel, Nvidia, IBM, HPE, etc.)
• Energy efficient, green computing (Intel, AMD, ARM, etc.)

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