Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userTheoretical Analysis and Evaluation of NoCs with Weighted Round-Robin Arbitration
140
0
0.0
(
0
)
Added by
Sumit Mandal
Publication date
2021
fields
Informatics Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
Fast and accurate performance analysis techniques are essential in early design space exploration and pre-silicon evaluations, including software eco-system development. In particular, on-chip communication continues to play an increasingly important role as the many-core processors scale up. This paper presents the first performance analysis technique that targets networks-on-chip (NoCs) that employ weighted round-robin (WRR) arbitration. Besides fairness, WRR arbitration provides flexibility in allocating bandwidth proportionally to the importance of the traffic classes, unlike basic round-robin and priority-based arbitration. The proposed approach first estimates the effective service time of the packets in the queue due to WRR arbitration. Then, it uses the effective service time to compute the average waiting time of the packets. Next, we incorporate a decomposition technique to extend the analytical model to handle NoC of any size. The proposed approach achieves less than 5% error while executing real applications and 10% error under challenging synthetic traffic with different burstiness levels.
rate research
Read More
Networks-on-Chip (NoCs) used in commercial many-core processors typically incorporate priority arbitration. Moreover, they experience bursty traffic due to application workloads. However, most state-of-the-art NoC analytical performance analysis techniques assume fair arbitration and simple traffic models. To address these limitations, we propose an analytical modeling technique for priority-aware NoCs under bursty traffic. Experimental evaluations with synthetic and bursty traffic show that the proposed approach has less than 10% modeling error with respect to cycle-accurate NoC simulator.
Priority-aware networks-on-chip (NoCs) are used in industry to achieve predictable latency under different workload conditions. These NoCs incorporate deflection routing to minimize queuing resources within routers and achieve low latency during low traffic load. However, deflected packets can exacerbate congestion during high traffic load since they consume the NoC bandwidth. State-of-the-art analytical models for priority-aware NoCs ignore deflected traffic despite its significant latency impact during congestion. This paper proposes a novel analytical approach to estimate end-to-end latency of priority-aware NoCs with deflection routing under bursty and heavy traffic scenarios. Experimental evaluations show that the proposed technique outperforms alternative approaches and estimates the average latency for real applications with less than 8% error compared to cycle-accurate simulations.
Star sampling (SS) is a random sampling procedure on a graph wherein each sample consists of a randomly selected vertex (the star center) and its one-hop neighbors (the star endpoints). We consider the use of star sampling to find any member of an arbitrary target set of vertices in a graph, where the figure of merit (cost) is either the expected number of samples (unit cost) or the expected number of star centers plus star endpoints (linear cost) until a vertex in the target set is encountered, either as a star center or as a star point. We analyze this performance measure on three related star sampling paradigms: SS with replacement (SSR), SS without center replacement (SSC), and SS without star replacement (SSS). We derive exact and approximate expressions for the expected unit and linear costs of SSR, SSC, and SSS on Erdos-Renyi (ER) graphs. Our results show there is i) little difference in unit cost, but ii) significant difference in linear cost, across the three paradigms. Although our results are derived for ER graphs, experiments on real-world graphs suggest our performance expressions are reasonably accurate for non-ER graphs.
Quantum key distribution (QKD) offers the possibility for two individuals to communicate a securely encrypted message. From the time of its inception in 1984 by Bennett and Brassard, QKD has been the result of intense research. One technical challenge is the monitoring of signal disturbance in a QKD system to bound the information leakage towards an unwanted eavesdropper. Recently, the round-robin differential phase-shift (RRDPS) protocol, which encodes bits of information in a high-dimensional state space, was proposed to solve this exact problem. Since its introduction, many realizations of the RRDPS protocol were demonstrated using trains of coherent pulses. Here, we propose and experimentally demonstrate an implementation of the RRDPS protocol using the photonic orbital angular momentum degree of freedom. In particular, we show that Alices generation stage and Bobs detection stage can each be reduced to a single phase element, greatly simplifying its implementation. Our scheme offers a practical demonstration of the RRDPS protocol which will suppress the need for monitoring signal disturbance in free-space channels.
In this paper we have used one 2 variable Boolean function called Rule 6 to define another beautiful transformation named as Extended Rule-6. Using this function we have explored the algebraic beauties and its application to an efficient Round Robin Tournament (RRT) routine for 2k (k is any natural number) number of teams. At the end, we have thrown some light towards any number of teams of the form nk where n, k are natural numbers.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
