Multi-Partner Project: Architectures and Design Methodologies to Accelerate AI Workloads. The ICSC Flagship 2 Project

Recent pre-exascale and exascale supercomputers have driven the development of increasingly sophisticated AI models for diverse applications, including image recognition and classification, natural language processing, and generative AI. These applications require specialized hardware accelerators, to handle the heavy computational demands of AI algorithms in an energy-efficient manner. Today, AI accelerators are deployed across various systems, from low-power edge devices to large-scale servers, high-performance computing (HPC) infrastructures, and data centers. The primary objective of the ICSC Flagship 2 project, discussed in this paper, is to develop heterogeneous hardware platforms optimized to accelerate HPC and big data applications. Specifically, this paper provides an overview of the key challenges addressed and the achievements realized at the current intermediate stage of the ICSC Flagship 2 project focused on architectures, technologies, and design methodologies to design efficient hardware accelerators for AI workloads, such as deep learning (DL) and transformer models.