相关论文: Architecture-Aware Optimization of an HEVC decoder…

Analog to digital converters (ADCs) are a major contributor to the power consumption of multiple-input multiple-output (MIMO) receivers in large bandwidth millimeter-wave systems. Prior works have considered two mitigating solutions to…

Given their increasing size and complexity, the need for efficient execution of deep neural networks has become increasingly pressing in the design of heterogeneous High-Performance Computing (HPC) and edge platforms, leading to a wide…

Video compression is widely used in digital television, surveillance systems, and virtual reality. Real-time video decoding is crucial in practical scenarios. Recently, neural video compression (NVC) combines traditional coding with deep…

Edge computing must be capable of executing computationally intensive algorithms, such as Deep Neural Networks (DNNs) while operating within a constrained computational resource budget. Such computations involve Matrix Vector…

Heterogeneous systems have become one of the most common architectures today, thanks to their excellent performance and energy consumption. However, due to their heterogeneity they are very complex to program and even more to achieve…

Dealing with asymmetry in the architecture opens a plethora of questions from the perspective of scheduling task-parallel applications, and there exist early attempts to address this problem via ad-hoc strategies embedded into a runtime…

For reasons of both performance and energy efficiency, high-performance computing (HPC) hardware is becoming increasingly heterogeneous. The OpenCL framework supports portable programming across a wide range of computing devices and is…

Heterogeneous architectures have emerged as a promising alternative for homogeneous architectures to improve the energy-efficiency of computer systems. Composite Cores Architecture (CCA), a class of dynamic heterogeneous architectures…

Most commercial embedded devices have been deployed with a single processor architecture. The code size and complexity of applications running on embedded devices are rapidly increasing due to the emergence of application business models…

We have developed a quantum annealing processor, based on an array of tunably coupled rf-SQUID flux qubits, fabricated in a superconducting integrated circuit process [1]. Implementing this type of processor at a scale of 512 qubits and…

In order to mitigate the long processing delay and high energy consumption of mobile augmented reality (AR) applications, mobile edge computing (MEC) has been recently proposed and is envisioned as a promising means to deliver better…

In a high-speed coherent optical transmission system, typically the signals obtained at the receiver front-end are digitized using very high-speed ADCs and then processed in the digital domain to remove optical channel impairments. In this…

Modern computer systems typically conbine multicore CPUs with accelerators like GPUs for inproved performance and energy efficiency. However, these sys- tems suffer from poor performance portability, code tuned for one device must be…

Versatile Video Coding (VVC) is the next generation video coding standard expected by the end of 2020. Compared to its predecessor, VVC introduces new coding tools to make compression more efficient at the expense of higher computational…

Transformers, while revolutionary, face challenges due to their demanding computational cost and large data movement. To address this, we propose HyFlexPIM, a novel mixed-signal processing-in-memory (PIM) accelerator for inference that…

The high volume of data transmission between the edge sensor and the cloud processor leads to energy and throughput bottlenecks for resource-constrained edge devices focused on computer vision. Hence, researchers are investigating different…

Mainstream image and video coding standards -- including state-of-the-art codecs like H.266/VVC, AVS3, and AV1 -- adopt a block-based hybrid coding framework. While this framework facilitates straightforward optimization for Peak…

Low-resolution analog-to-digital converters (ADCs) have emerged as an efficient solution for massive multiple-input multiple-output (MIMO) systems to reap high data rates with reasonable power consumption and hardware complexity. In this…

Artificial intelligence and machine learning models deployed on edge devices, e.g., for quality control in Additive Manufacturing (AM), are frequently small in size. Such models usually have to deliver highly accurate results within a short…

Large-scale multiple-input and multiple-output (MIMO) systems are capable of achieving high date rate. However, given the high hardware cost and excessive power consumption of massive MIMO systems, as a remedy, intelligent metasurfaces have…