A methodology for correct-by-construction latency insensitive design
ICCAD '99 Proceedings of the 1999 IEEE/ACM international conference on Computer-aided design
Coping with Latency in SOC Design
IEEE Micro
Beyond Moore's Law: The Interconnect Era
Computing in Science and Engineering
Issues in Implementing Latency Insensitive Protocols
Proceedings of the conference on Design, automation and test in Europe - Volume 2
A new approach to latency insensitive design
Proceedings of the 41st annual Design Automation Conference
Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design
Topology-based optimization of maximal sustainable throughput in a latency-insensitive system
Proceedings of the 44th annual Design Automation Conference
Performance optimization of elastic systems using buffer resizing and buffer insertion
Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design
Theory of latency-insensitive design
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Performance analysis of latency-insensitive systems
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Topology-Based Performance Analysis and Optimization of Latency-Insensitive Systems
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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As fabrication process exploits even deeper submicron technology, global interconnect delay is becoming one of the most critical performance obstacles in system-on-chip (SoC) designs nowadays. Recent years latency-insensitive system (LIS), which enables multicycle communication to tolerate variant interconnect delay without substantially modifying pre-designed IP cores, has been proposed to conquer this issue. However, imbalanced interconnect latency and communication back-pressure residing in an LIS still degrade system throughput. In this paper, we present a throughput optimization technique with minimal queue insertion. We first model a given LIS as a quantitative graph (QG), which can be further compacted using the proposed techniques, so that much bigger problems can be handled. On top of QG, the optimal solution with minimal queue size can be achieved through integer linear programming based on the proposed constraint formulation in an acceptable runtime. The experimental results show that our approach can deal with moderately large systems in a reasonable runtime and save about 28% of queues compared to the prior art.