217 citations · 1.3k across the 49 of their papers we have counts for
8 papers · 1 filter
Xel-FPGAs: An End-to-End Automated Exploration Framework for Approximate Accelerators in FPGA-Based Systems
Bharath Srinivas Prabakaran, Vojtech Mrazek, Zdenek Vasicek +2
Generation and exploration of approximate circuits and accelerators has been a prominent research domain to achieve energy-efficiency and/or performance improvements. This research…
SparkXD: A Framework for Resilient and Energy-Efficient Spiking Neural Network Inference using Approximate DRAM
Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
Spiking Neural Networks (SNNs) have the potential for achieving low energy consumption due to their biologically sparse computation. Several studies have shown that the off-chip me…
DNN-Life: An Energy-Efficient Aging Mitigation Framework for Improving the Lifetime of On-Chip Weight Memories in Deep Neural Network Hardware Architectures
Muhammad Abdullah Hanif, Muhammad Shafique
Negative Biased Temperature Instability (NBTI)-induced aging is one of the critical reliability threats in nano-scale devices. This paper makes the first attempt to study the NBTI…
Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead
Maurizio Capra, Beatrice Bussolino, Alberto Marchisio +3
Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning (DL) is already present in many applications ranging from computer vision for medicine to au…
ApproxFPGAs: Embracing ASIC-Based Approximate Arithmetic Components for FPGA-Based Systems
Bharath Srinivas Prabakaran, Vojtech Mrazek, Zdenek Vasicek +2
There has been abundant research on the development of Approximate Circuits (ACs) for ASICs. However, previous studies have illustrated that ASIC-based ACs offer asymmetrical gains…
DRMap: A Generic DRAM Data Mapping Policy for Energy-Efficient Processing of Convolutional Neural Networks
Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
Many convolutional neural network (CNN) accelerators face performance- and energy-efficiency challenges which are crucial for embedded implementations, due to high DRAM access late…
Proactive Aging Mitigation in CGRAs through Utilization-Aware Allocation
Marcelo Brandalero, Bernardo Neuhaus Lignati, Antonio Carlos Schneider Beck +2
Resource balancing has been effectively used to mitigate the long-term aging effects of Negative Bias Temperature Instability (NBTI) in multi-core and Graphics Processing Unit (GPU…
Architectural-Space Exploration of Heterogeneous Reliability and Checkpointing Modes for Out-of-Order Superscalar Processors
Bharath Srinivas Prabakaran, Mihika Dave, Florian Kriebel +2
Reliability has emerged as a key topic of interest for researchers around the world to detect and/or mitigate the side effects of decreasing transistor sizes, such as soft errors.…