A
Ali Ebrahim
Researcher at University of Edinburgh
Publications - 20
Citations - 275
Ali Ebrahim is an academic researcher from University of Edinburgh. The author has contributed to research in topics: Field-programmable gate array & Control reconfiguration. The author has an hindex of 11, co-authored 18 publications receiving 257 citations.
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Journal ArticleDOI
R3TOS: A Novel Reliable Reconfigurable Real-Time Operating System for Highly Adaptive, Efficient, and Dependable Computing on FPGAs
Xabier Iturbe,Khaled Benkrid,Chuan Hong,Ali Ebrahim,Raul Torrego,Imanol Martinez,Tughrul Arslan,Jon Perez +7 more
TL;DR: R3TOS provides systematic OS support for FPGAs, allowing the exploitation of some of the most advanced capabilities of FPGA technology by inexperienced users, with the dual objective of improving computation density and circumventing damaged resources on theFPGA.
Proceedings ArticleDOI
A novel high-performance fault-tolerant ICAP controller
TL;DR: This paper presents a novel high performance and fault-tolerant ICAP controller which can operate at a high speed and recover from emerging faults, and demonstrates the use of Triple Modular Redundancy (TMR) in some of theICAP controller components which have the ability to reconfigure the rest of the IC AP controller when faults are detected.
Journal ArticleDOI
Runtime Scheduling, Allocation, and Execution of Real-Time Hardware Tasks onto Xilinx FPGAs Subject to Fault Occurrence
TL;DR: A novel way to exploit the computation capabilities delivered by modern Field-Programmable Gate Arrays (FPGAs) not only towards a higher performance, but also towards an improved reliability through a set of novel algorithms.
Journal ArticleDOI
Efficient On-Chip Task Scheduler and Allocator for Reconfigurable Operating Systems
TL;DR: A novel fault-tolerant allocating algorithm called “best-fit empty area compact (BF-EAC),” and its on-chip implementation on a Xilinx Virtex-4 field-programmable gate array (FPGA), which circumvents emerging faults while maintaining more compact empty areas for emerging tasks.
Journal ArticleDOI
Novel dynamic partial reconfiguration implementation of k-means clustering on FPGAs: comparative results with GPPs and GPUs
TL;DR: A parameterized implementation of the K-means clustering algorithm in Field Programmable Gate Array (FPGA) is presented and compared with previous FPGA implementation as well as recent implementations on Graphics Processing Units (GPUs) and GPPs.