Abstract: Multiplication is a fundamental operation in neural network models. However, signed multibit multiplication and accumulation (MAC) pose significant challenges, primarily due to the ...

Abstract: Field-programmable gate arrays (FPGAs) can efficiently implement custom applications via their embedded digital signal processor (DSP) slices, including binary multipliers. An increasing ...

Cyclops is a parallel (distributed-memory) numerical library for multidimensional arrays (tensors) in C++ and Python. Quick documentation links: C++ and Python. Broadly, Cyclops provides tensor ...

Abstract— Multipliers are crucial components in processors and arithmetic logic units. The performance of microsystems, microcontrollers, and DSP processors is often evaluated based on the number of ...

Multi-core processors theoretically can run many threads of code in parallel, but some categories of operation currently bog down attempts to raise overall performance by parallelizing computing. Is ...

Over the past decade, Graphics Processing Units (GPUs) have revolutionized high-performance computing, playing pivotal roles in advancing fields like IoT, autonomous ...

This repository includes a pure Vitis HLS implementation of matrix-matrix multiplication (A*B=C) for Xilinx FPGAs, using Xilinx Vitis to instantiate memory and PCIe controllers and interface with the ...

Hardware architectures composed of resistive cross-point device arrays can provide significant power and speed benefits for deep neural network training workloads using stochastic gradient descent ...