BetaArc

BetaArc is a reconfigurable computing platform designed for high-performance computing (HPC) and artificial intelligence (AI) applications. The platform is based on a fine-grained reconfigurable architecture, allowing for the rapid adaptation of hardware configurations to meet changing workload demands.

BetaArc was developed by Honeywell International, in collaboration with researchers from the University of Illinois and the University of California, Los Angeles (UCLA). The platform uses a proprietary reconfigurable fabric, which consists of a large number of small, interconnected processing elements. This fabric can be dynamically reconfigured to support a wide range of workloads, from low-level data processing to complex AI inference tasks.

The BetaArc platform is designed to be highly scalable, with a maximum capacity of over 100,000 processing elements. The platform can be used in a variety of applications, including computer vision, machine learning, and scientific simulation. To support the development of AI and HPC workloads, the BetaArc platform provides a range of tools and frameworks, including a high-level programming language and a software development kit (SDK).

BetaArc has been successfully tested in a range of applications, including image recognition and object detection, where it demonstrates performance gains of up to 100 times compared to traditional general-purpose computing platforms. The platform's reconfigurable architecture also enables the efficient execution of multiple workloads simultaneously, making it suitable for a wide range of HPC and AI applications. However, the commercial availability and feasibility of BetaArc for broader adoption have not been publicly disclosed.