Track on Efficieny Enhencement for Artificial Intelligence and High-Performance Computing
November 20-22, 2024
Ciudad Jardin in the province of Ilo (National University of Moquegua), PERU
Held in conjunction with the
11th International Conference on Information Management and Big Data (SIMBig 2024)

High-speed parallel processes of complex computations on clusters are the right tools to solve specific large-scale computing problems related to artificial intelligence (AI) like the implementation of large-scale deep learning models. The expectations from AI are very high, and significant progresses are being made. Powerful AI methods like Deep Learning together with the processing of large-scale datasets are computationally expensive, hence the need for high performance computing. Considering the advances in storage, memory, CPU, and GPU (hybrid computing), the EE-AI-HPC Track at SIMBig 2023 stands as a forum for computer scientists and software engineers who work on parallel and accelerated programming, HPC as a service (simplifying deployments on HPC clusters), mathematical frameworks, interaction between AI and data models, industrial and scientific simulations, to participate and share their contributions on HPC as a support for AI. This wtrack is an opportunity for application designers and computer architects to discuss new AI/HPC techniques and emerging applications as well as their implications on cutting-edge scientific and technical activities.
Authors are invited to submit original and innovative papers that break new ground and present insightful results based on your skills and experience in High-Performance Computing for Artificial Intelligence. Topics of interest for EE-AI-HPC 2023 include (but are not limited to):

Submissions must be in English following Springer's guidelines related to the series Lecture Notes in Computer Science (LNCS), and provided in pdf format. We will consider two paper categories depending on the length (including bibliography and well‐marked appendices): “short paper” (between 6 and 8 pages) or “full paper” (no longer than 15 pages). In addition, submission is double-blind. Therefore, authors need to ensure that their manuscripts are prepared in a way that does not reveal their identity. Follow this instruction to avoid an automatic rejection of the submission.

Organizers
		Juan Antonio Lossio-Ventura (National Institutes of Health (NIH), USA)
		Claude Tadonki (MINES Paris - PSL, Paris, France)
		Hugo Alatrista Salas (Pontificia Universidad Católica del Perú, Perú)