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How Parallel Processing Solves Our Biggest Computational Problems


Take all the help you can get. If parallel computing has a central tenet, that might be it. Some of the crazy-complex computations asked of today's hardware are so demanding that the compute burden must be borne by multiple processors, effectively "parallelizing" whatever task is being performed. Perhaps the most notable push toward parallelism happened around 2006, when tech hardware powerhouse Nvidia approached Wen-mei Hwu, a professor of electrical and computer engineering at the University of Illinois-Urbana Champaign. Nvidia was designing graphics processing units (GPUs) -- which, thanks to large numbers of threads and cores, had far higher memory bandwidth than the traditional central processing unit (CPUs) -- as a way to process huge numbers of pixels.

Quantum Computing Market Worth $283 Million by 2024 - Exclusive Report by MarketsandMarkets


According to the new market research report "Quantum Computing Market by Offering (Systems and Consulting Solutions), End-User Industry, and Geography; QCaaS Market by Application (Optimization, Machine Learning, and Material Simulation) and Geography - Global Forecast to 2024", published by MarketsandMarkets, the Quantum Computing Market is expected to grow from USD 93 million by 2019 to USD 283 million by 2024; it is estimated at a CAGR of 24.9%. Whereas, the market for QCaaS is expected to grow from USD 4 million by 2019 to USD 13 million by 2024 at a CAGR of 26.8%. The need for robust computing that has the potential to overcome complexities involved in cancer-specific drug discovery and in evaluating portfolio risk is a major factor contributing to the market growth. Quantum computing is used for material simulation in various industries, such as healthcare, automotive, entertainment, banking and finance, and defense. Companies such as D-Wave Systems Inc. (Canada), 1QB Information Technologies Inc. (Canada), and QxBranch, LLC (US) are working toward providing a platform to enhance the availability, usability, and accessibility of quantum computers in the material simulation applications.