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DTSTAMP:20250822T115806Z
LOCATION:Room 5.2D02
DTSTART;TZID=Europe/Stockholm:20250616T143000
DTEND;TZID=Europe/Stockholm:20250616T163000
UID:submissions.pasc-conference.org_PASC25_sess132@linklings.com
SUMMARY:MS2F - Emerging Computing Technologies for Next-Generation High-Pe
 rformance Computing
DESCRIPTION:High-performance computing (HPC) is evolving rapidly to meet t
 he growing demands of complex scientific, engineering, and industrial appl
 ications. As data volumes expand exponentially and simulations become incr
 easingly intricate, the future of HPC will rely on cutting-edge hardware, 
 innovative architectures, and software-driven optimizations to boost proce
 ssing power, efficiency, and scalability. At the same time, Artificial Int
 elligence (AI) is transforming HPC by enhancing computational efficiency t
 hrough predictive models and adaptive processing techniques. However, this
  integration also intensifies the need for computational resources, creati
 ng challenges such as rising energy consumption and the efficient manageme
 nt of resources. Addressing these issues requires exploring novel computin
 g platforms that balance high performance with sustainability. This minisy
 mposium will examine emerging technologies, including Quantum Computing, E
 lectronic Neuromorphic Computing, and Photonic Computing, which are at var
 ious stages of development. By analyzing these advancements and their pote
 ntial applications, we aim to outline a roadmap for the next generation of
  HPC technologies. The discussion will emphasize their transformative impa
 ct on diverse fields, highlighting how these innovative solutions could sh
 ape the future of computing over the next decade.\n\nProbing and Benchmark
 ing Quantum Devices with Randomized Measurements\n\nQuantum computing has 
 rapidly evolved in recent years, with platforms ranging from superconducti
 ng qubits and trapped ions to photonic and neutral atom systems. These div
 erse approaches offer unique strengths and challenges, driving the need fo
 r reliable methods to assess and optimize device perform...\n\n\nAndreas E
 lben (Paul Scherrer Institute)\n---------------------\nIntegrated Photonic
 s for High-Speed Neuromorphic Processing\n\nAlthough modern optical commun
 ications typically rely on digital signals, analog photonics has been an a
 ctive field of research over the last decades. In parallel, photonics for 
 computing experienced an intermittent research interest. Recent breakthrou
 ghs in artificial intelligence have sparked atte...\n\n\nNicola Andriolli 
 (University of Pisa)\n---------------------\nDeep Neural Network Inference
  with Analog In-Memory Computing\n\nThe need to repeatedly shuttle around 
 synaptic weight values from memory to processing units has been a key sour
 ce of energy inefficiency associated with hardware implementation of artif
 icial neural networks. Analog in-memory computing (AIMC) with spatially in
 stantiated synaptic weights holds high p...\n\n\nManuel Le Gallo (IBM Rese
 arch Europe)\n---------------------\nOpen Discussion: Emerging Computing T
 echnologies for Next-Generation High-Performance Computing\n\nThis panel w
 ill explore emerging computing technologies that are shaping the future of
  high-performance computing (HPC), including advances in architectures, ac
 celerators, and software ecosystems. Experts from academia and industry wi
 ll discuss the opportunities and challenges in scaling next-genera...\n\n\
 nNicola Andriolli (University of Pisa), Manuel Le Gallo (IBM Research Euro
 pe), and Andreas Elben (Paul Scherrer Institute)\n\nDomain: Engineering\n\
 nSession Chairs: Mauro Bianco (ETH Zurich / CSCS, ETH Zurich) and Nur Aima
 n Fadel (ETH Zurich / CSCS)
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