M
Manil Dev Gomony
Researcher at Bell Labs
Publications - 26
Citations - 301
Manil Dev Gomony is an academic researcher from Bell Labs. The author has contributed to research in topics: Computer science & Memory controller. The author has an hindex of 9, co-authored 17 publications receiving 277 citations. Previous affiliations of Manil Dev Gomony include Eindhoven University of Technology.
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Journal ArticleDOI
Virtual execution platforms for mixed-time-criticality systems: the CompSOC architecture and design flow
Kees Goossens,Arnaldo Azevedo,Karthik Chandrasekar,Manil Dev Gomony,Sven Goossens,Martijn Koedam,Yonghui Li,Davit Mirzoyan,Anca Molnos,Ashkan Beyranvand Nejad,Andrew Nelson,Shubhendu Sinha +11 more
TL;DR: This paper introduces the composability and predictability concepts, why they help, and how they are implemented in the different resources of the CompSOC architecture, and defines a design flow that allows real-time cyclo-static dataflow applications to be automatically mapped, verified, and executed.
Proceedings ArticleDOI
Architecture and optimal configuration of a real-time multi-channel memory controller
TL;DR: A real-time multi-channel memory controller architecture with a new programmable Multi-Channel Interleaver unit and a novel method for logical-to-physical address translation that enables inter-leaving memory requests across multiple memory channels at different granularities are contributed.
Journal ArticleDOI
Leveraging 802.11n frame aggregation to enhance QoS and power consumption in Wi-Fi networks
TL;DR: This paper designs CA-DFA, an algorithm that, using only information available at layer two, adapts the amount of 802.11n aggregation used by a Wi-Fi station according to the level of congestion in the network, and demonstrates the benefits of this algorithm in terms of QoS, energy efficiency and network capacity with respect to state of the art alternatives.
Journal ArticleDOI
A Globally Arbitrated Memory Tree for Mixed-Time-Criticality Systems
TL;DR: The performance of GAMT is compared with centralized implementations and it is shown that it can run up to four times faster and have over 51 and 37 percent reduction in area and power consumption, respectively, for a given bandwidth.
Proceedings ArticleDOI
DRAM selection and configuration for real-time mobile systems
TL;DR: This paper analyzes the worst-case bandwidth, average-case execution time, and power consumption of mobile DRAMs across three generations: L PDDR, LPDDR2 and Wide-IO-based 3D-stacked DRAM, and proposes a methodology for selecting memory configurations in real-time mobile systems.