13,763 research outputs found

    Throughput-driven floorplanning with wire pipelining

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    The size of future high-performance SoC is such that the time-of-flight of wires connecting distant pins in the layout can be much higher than the clock period. In order to keep the frequency as high as possible, the wires may be pipelined. However, the insertion of flip-flops may alter the throughput of the system due to the presence of loops in the logic netlist. In this paper, we address the problem of floorplanning a large design where long interconnects are pipelined by inserting the throughput in the cost function of a tool based on simulated annealing. The results obtained on a series of benchmarks are then validated using a simple router that breaks long interconnects by suitably placing flip-flops along the wires

    A scalable multi-core architecture with heterogeneous memory structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs)

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    Neuromorphic computing systems comprise networks of neurons that use asynchronous events for both computation and communication. This type of representation offers several advantages in terms of bandwidth and power consumption in neuromorphic electronic systems. However, managing the traffic of asynchronous events in large scale systems is a daunting task, both in terms of circuit complexity and memory requirements. Here we present a novel routing methodology that employs both hierarchical and mesh routing strategies and combines heterogeneous memory structures for minimizing both memory requirements and latency, while maximizing programming flexibility to support a wide range of event-based neural network architectures, through parameter configuration. We validated the proposed scheme in a prototype multi-core neuromorphic processor chip that employs hybrid analog/digital circuits for emulating synapse and neuron dynamics together with asynchronous digital circuits for managing the address-event traffic. We present a theoretical analysis of the proposed connectivity scheme, describe the methods and circuits used to implement such scheme, and characterize the prototype chip. Finally, we demonstrate the use of the neuromorphic processor with a convolutional neural network for the real-time classification of visual symbols being flashed to a dynamic vision sensor (DVS) at high speed.Comment: 17 pages, 14 figure

    Cell replication and redundancy elimination during placement for cycle time optimization

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    This paper presents a new timing driven approach for cell replication tailored to the practical needs of standard cell layout design. Cell replication methods have been studied extensively in the context of generic partitioning problems. However, until now it has remained unclear what practical benefit can be obtained from this concept in a realistic environment for timing driven layout synthesis. Therefore, this paper presents a timing driven cell replication procedure, demonstrates its incorporation into a standard cell placement and routing tool and examines its benefit on the final circuit performance in comparison with conventional gate or transistor sizing techniques. Furthermore, we demonstrate that cell replication can deteriorate the stuck-at fault testability of circuits and show that stuck-at redundancy elimination must be integrated into the placement procedure. Experimental results demonstrate the usefulness of the proposed methodology and suggest that cell replication should be an integral part of the physical design flow complementing traditional gate sizing techniques
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