Xilinx

About: Xilinx is a company organization based out in San Jose, California, United States. It is known for research contribution in the topics: Programmable logic device & Integrated circuit. The organization has 2814 authors who have published 5275 publications receiving 91373 citations. The organization is also known as: Xilinx, Inc. & Xilinx (United States).

Experiment-Driven Characterization of Full-Duplex Wireless Systems

Abstract: We present an experiment-based characterization of passive suppression and active self-interference cancellation mechanisms in full-duplex wireless communication systems. In particular, we consider passive suppression due to antenna separation at the same node, and active cancellation in analog and/or digital domain. First, we show that the average amount of cancellation increases for active cancellation techniques as the received self-interference power increases. Our characterization of the average cancellation as a function of the self-interference power allows us to show that for a constant signal-to-interference ratio at the receiver antenna (before any active cancellation is applied), the rate of a full-duplex link increases as the self-interference power increases. Second, we show that applying digital cancellation after analog cancellation can sometimes increase the self-interference, and thus digital cancellation is more effective when applied selectively based on measured suppression values. Third, we complete our study of the impact of self-interference cancellation mechanisms by characterizing the probability distribution of the self-interference channel before and after cancellation.

FINN: A Framework for Fast, Scalable Binarized Neural Network Inference

Abstract: Research has shown that convolutional neural networks contain significant redundancy, and high classification accuracy can be obtained even when weights and activations are reduced from floating point to binary values. In this paper, we present FINN, a framework for building fast and flexible FPGA accelerators using a flexible heterogeneous streaming architecture. By utilizing a novel set of optimizations that enable efficient mapping of binarized neural networks to hardware, we implement fully connected, convolutional and pooling layers, with per-layer compute resources being tailored to user-provided throughput requirements. On a ZC706 embedded FPGA platform drawing less than 25 W total system power, we demonstrate up to 12.3 million image classifications per second with 0.31 μs latency on the MNIST dataset with 95.8% accuracy, and 21906 image classifications per second with 283 μs latency on the CIFAR-10 and SVHN datasets with respectively 80.1% and 94.9% accuracy. To the best of our knowledge, ours are the fastest classification rates reported to date on these benchmarks.

Configurable electrical circuit having configurable logic elements and configurable interconnects

Abstract: A configurable logic array comprises a plurality of configurable logic elements variably interconnected in response to control signals to perform a selected logic function. Each configurable logic element in the array is in itself capable of performing any one of a plurality of logic functions depending upon the control information placed in the configurable logic element. Each configurable logic element can have its function varied even after it is installed in a system by changing the control information placed in that element. Structure is provided for storing control information and providing access to the stored control information to allow each configurable logic element to be properly configured prior to the initiation of operation of the system of which the array is a part. Novel interconnection structures are provided to facilitate the configuring of each logic element.

Checking Safety Properties Using Induction and a SAT-Solver

Abstract: We take a fresh look at the problem of how to check safety properties of finite state machines. We are particularly interested in checking safety properties with the help of a SAT-solver. We describe some novel induction-based methods, and show how they are related to more standard fixpoint algorithms for invariance checking. We also present preliminary experimental results in the verification of FPGA cores. This demonstrates the practicality of combining a SAT-solver with induction for safety property checking of hardware in a real design flow.

High-Level Synthesis for FPGAs: From Prototyping to Deployment

Abstract: Escalating system-on-chip design complexity is pushing the design community to raise the level of abstraction beyond register transfer level. Despite the unsuccessful adoptions of early generations of commercial high-level synthesis (HLS) systems, we believe that the tipping point for transitioning to HLS msystem-on-chip design complexityethodology is happening now, especially for field-programmable gate array (FPGA) designs. The latest generation of HLS tools has made significant progress in providing wide language coverage and robust compilation technology, platform-based modeling, advancement in core HLS algorithms, and a domain-specific approach. In this paper, we use AutoESL's AutoPilot HLS tool coupled with domain-specific system-level implementation platforms developed by Xilinx as an example to demonstrate the effectiveness of state-of-art C-to-FPGA synthesis solutions targeting multiple application domains. Complex industrial designs targeting Xilinx FPGAs are also presented as case studies, including comparison of HLS solutions versus optimized manual designs. In particular, the experiment on a sphere decoder shows that the HLS solution can achieve an 11-31% reduction in FPGA resource usage with improved design productivity compared to hand-coded design.