For decades, Java has been the enterprise world's go-to programming language—the reliable, if somewhat verbose, workhorse powering everything from banking systems to e-commerce platforms. But when the ...

Compute-In-memory (CIM) has shown significant potential in efficiently accelerating deep neural networks (DNNs) at the edge, particularly in speeding up quantized models for inference applications.

Computing-in-memory (CIM) chips have demonstrated promising high energy efficiency on multiply–accumulate (MAC) operations for artificial intelligence (AI) applications. Though integral (INT) CIM ...

This paper presents a high-throughput, low-latency 4096-point FFT/IFFT hardware design tailored for 5G applications. Using the radix-16 FFT algorithm, the architecture efficiently supports both FFT ...

Neural architecture search (NAS) automates neural network design by using optimization algorithms to navigate architecture spaces, reducing the burden of manual architecture design. While NAS has ...

However, the Transformer architecture's high computational demands limit its scalability and deployment on resource-constrained platforms, hindering its practical applications in on-device multimedia ...

In recent years, point cloud analysis methods based on the Transformer architecture have made significant progress, particularly in the context of multimedia applications such as 3D modeling, virtual ...

With the increasing complexity of software business, the traditional layered architecture based on MVC mode gradually exposes the shortcomings of tight coupling of service layer logic, difficult ...