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Rohith M. K.

dblp:298/3043 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Memory systems · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Memory systems › memory bandwidth management
memory bandwidth reduction
0.612022
FlitZip: Effective Packet Compression for NoC in MultiProcessor System-on-Chip · IEEE Trans. Parallel Distributed Syst. 2022
Memory systems › memory hierarchy
cache hierarchy
0.212022
FlitZip: Effective Packet Compression for NoC in MultiProcessor System-on-Chip · IEEE Trans. Parallel Distributed Syst. 2022
YearPublicationVenuePosition
2022 FlitZip: Effective Packet Compression for NoC in MultiProcessor System-on-Chip
abstract
Applications running on Network on Chip (NoC) based multicore systems demand increased on-chip network bandwidth that can cater to the need for intensive communication among the cores and caches. Due to strict area and power budget, the bandwidth offered by NoC is very limited. Data-intensive and communication-centric applications on encountering a cache miss lead to a considerable burden on the underlying network for transferring blocks from multiple cache hierarchies to the requesting core as packets. This increases the packet transmission latency, thereby slowing down the system performance. Also, NoC being the highest component of power consumption after the cores, an increase in packets increases the dynamic power consumption of NoC. The article proposes FlitZip that addresses the problem by reducing on-chip traffic through compressing network packets. Hence, the compressed packet requires less bandwidth during its transfer, reducing the network's power consumption. Experimental analysis shows that FlitZip achieves a better compression ratio of 52 percent, reduces packet latency and bandwidth utilization by 19.28 and 27 percent, respectively. It also reduces the area and power consumption of the de/compression units by 53.33 and 62.3 percent, respectively, compared to the state-of-the-art packet compression technique, NoΔ.
Dipika Deb, Rohith M. K., John Jose
IEEE Trans. Parallel Distributed Syst.2