Lecture

Neuromorphic Computing: Challenges & Future

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In course

NX-450: Computational neurosciences: biophysics

The course introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies with a focus on the biophysical level. ...

Description

This lecture explores the challenges and future of neuromorphic computing, comparing digital computers and neuromorphic systems. It delves into the performance differences between SpiNNaker and NEST, highlighting the impact of numerical accuracy and hardware configurations. The presentation also discusses the Human Brain Project's Neuromorphic Computing Platform, offering insights into its usage and benefits. The instructor covers the evolution of computing, emphasizing the limitations of CMOS scaling and the need for alternative architectures. The lecture concludes by examining the potential of neuromorphic computing to complement traditional digital systems in the future.

Instructors (2)

Felix Schürmann

Felix Schürmann is co-director of the Blue Brain Project and involved in several research challenges of the European Human Brain Project. He studied physics at the University of Heidelberg, Germany, supported by the German National Academic Foundation. Later, as a Fulbright Scholar, he obtained his Master's degree (M.S.) in Physics from the State University of New York, Buffalo, USA, under the supervision of Richard Gonsalves. During these studies, he became curious about the role of different computing substrates and dedicated his master thesis to the simulation of quantum computing. He studied for his Ph.D. at the University of Heidelberg, Germany, under the supervision of Karlheinz Meier. For his thesis he co-designed an efficient implementation of a neural network in hardware.

Armando Romani

Official source

Ontological neighbourhood

Computer engineering

Hardware engineering: Microprocessors

Related concepts (32)

Computer

A computer is a machine that can be programmed to carry out sequences of arithmetic or logical operations (computation) automatically. Modern digital electronic computers can perform generic sets of operations known as programs. These programs enable computers to perform a wide range of tasks. A computer system is a nominally complete computer that includes the hardware, operating system (main software), and peripheral equipment needed and used for full operation.

Digital electronics

Digital electronics is a field of electronics involving the study of digital signals and the engineering of devices that use or produce them. This is in contrast to analog electronics and analog signals. Digital electronic circuits are usually made from large assemblies of logic gates, often packaged in integrated circuits. Complex devices may have simple electronic representations of Boolean logic functions. The binary number system was refined by Gottfried Wilhelm Leibniz (published in 1705) and he also established that by using the binary system, the principles of arithmetic and logic could be joined.

Digital media

In mass communication, digital media is any communication media that operate in conjunction with various encoded machine-readable data formats. Digital content can be created, viewed, distributed, modified, listened to, and preserved on a digital electronics device, including digital data storage media (in contrast to analog electronic media) and digital broadcasting. Digital defines as any data represented by a series of digits, and media refers to methods of broadcasting or communicating this information.

Multi-core processor

A multi-core processor is a microprocessor on a single integrated circuit with two or more separate processing units, called cores, each of which reads and executes program instructions. The instructions are ordinary CPU instructions (such as add, move data, and branch) but the single processor can run instructions on separate cores at the same time, increasing overall speed for programs that support multithreading or other parallel computing techniques.

Digital image processing

Digital image processing is the use of a digital computer to process s through an algorithm. As a subcategory or field of digital signal processing, digital image processing has many advantages over . It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the build-up of noise and distortion during processing. Since images are defined over two dimensions (perhaps more) digital image processing may be modeled in the form of multidimensional systems.

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