In this community review report, we discuss applications and techniques for fast machine
learning (ML) in science—the concept of integrating powerful ML methods into the real-time …

Field Programmable Gate Arrays (FPGAs) are spatial architectures with a heterogeneous
reconfigurable fabric. They are state-of-the-art for prototy**, telecommunications …

Recent studies on software tool manipulation with large language models (LLMs) mostly rely
on closed model APIs. The industrial adoption of these models is substantially constrained …

While systolic array architectures have the potential to deliver tremendous performance, it is
notoriously challenging to customize an efficient systolic array processor for a target …

With the end of both Dennard's scaling and Moore's law, computer users and researchers
are aggressively exploring alternative forms of computing in order to continue the …

As large language models (LLMs) like ChatGPT exhibited unprecedented machine
intelligence, it also shows great performance in assisting hardware engineers to realize …

Cloud providers such as Amazon and Microsoft have begun to support on-demand FPGA
acceleration in the cloud, and hardware vendors will support FPGAs in future processors. At …

Domain-specific hardware accelerators can provide orders of magnitude speedup and
energy efficiency over general purpose processors. However, they require extensive manual …

Special-purpose hardware accelerators are increasingly pivotal for sustaining performance
improvements in emerging applications, especially as the benefits of technology scaling …

The ubiquity of accelerators in high-performance computing has driven programming
complexity beyond the skill-set of the average domain scientist. To maintain performance …