49 citations · 123 across the 21 of their papers we have counts for
5 papers · 1 filter
On the Resilience of Deep Learning for Reduced-voltage FPGAs
Kamyar Givaki, Behzad Salami, Reza Hojabr +6
Deep Neural Networks (DNNs) are inherently computation-intensive and also power-hungry. Hardware accelerators such as Field Programmable Gate Arrays (FPGAs) are a promising solutio…
LEGaTO: Low-Energy, Secure, and Resilient Toolset for Heterogeneous Computing
B. Salami, K. Parasyris, A. Cristal +42
The LEGaTO project leverages task-based programming models to provide a software ecosystem for Made in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engi…
A Novel FPGA-Based High Throughput Accelerator For Binary Search Trees
Oyku Melikoglu, Oguz Ergin, Behzad Salami +3
This paper presents a deeply pipelined and massively parallel Binary Search Tree (BST) accelerator for Field Programmable Gate Arrays (FPGAs). Our design relies on the extremely pa…
Hardware Versus Software Fault Injection of Modern Undervolted SRAMs
Muhammet Abdullah Soyturk, Konstantinos Parasyris, Behzad Salami +3
To improve power efficiency, researchers are experimenting with dynamically adjusting the supply voltage of systems below the nominal operating points. However, production systems…
Evaluating Built-in ECC of FPGA on-chip Memories for the Mitigation of Undervolting Faults
Behzad Salami, Osman S. Unsal, Adrian Cristal Kestelman
Voltage underscaling below the nominal level is an effective solution for improving energy efficiency in digital circuits, e.g., Field Programmable Gate Arrays (FPGAs). However, fu…