12,867 research outputs found

    MORA - an architecture and programming model for a resource efficient coarse grained reconfigurable processor

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    This paper presents an architecture and implementation details for MORA, a novel coarse grained reconfigurable processor for accelerating media processing applications. The MORA architecture involves a 2-D array of several such processors, to deliver low cost, high throughput performance in media processing applications. A distinguishing feature of the MORA architecture is the co-design of hardware architecture and low-level programming language throughout the design cycle. The implementation details for the single MORA processor, and benchmark evaluation using a cycle accurate simulator are presented

    Quantum gate learning in engineered qubit networks: Toffoli gate with always-on interactions

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    We put forward a strategy to encode a quantum operation into the unmodulated dynamics of a quantum network without the need of external control pulses, measurements or active feedback. Our optimization scheme, inspired by supervised machine learning, consists in engineering the pairwise couplings between the network qubits so that the target quantum operation is encoded in the natural reduced dynamics of a network section. The efficacy of the proposed scheme is demonstrated by the finding of uncontrolled four-qubit networks that implement either the Toffoli gate, the Fredkin gate, or remote logic operations. The proposed Toffoli gate is stable against imperfections, has a high-fidelity for fault tolerant quantum computation, and is fast, being based on the non-equilibrium dynamics.Comment: 8 pages, 3 figure

    ARPA Whitepaper

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    We propose a secure computation solution for blockchain networks. The correctness of computation is verifiable even under malicious majority condition using information-theoretic Message Authentication Code (MAC), and the privacy is preserved using Secret-Sharing. With state-of-the-art multiparty computation protocol and a layer2 solution, our privacy-preserving computation guarantees data security on blockchain, cryptographically, while reducing the heavy-lifting computation job to a few nodes. This breakthrough has several implications on the future of decentralized networks. First, secure computation can be used to support Private Smart Contracts, where consensus is reached without exposing the information in the public contract. Second, it enables data to be shared and used in trustless network, without disclosing the raw data during data-at-use, where data ownership and data usage is safely separated. Last but not least, computation and verification processes are separated, which can be perceived as computational sharding, this effectively makes the transaction processing speed linear to the number of participating nodes. Our objective is to deploy our secure computation network as an layer2 solution to any blockchain system. Smart Contracts\cite{smartcontract} will be used as bridge to link the blockchain and computation networks. Additionally, they will be used as verifier to ensure that outsourced computation is completed correctly. In order to achieve this, we first develop a general MPC network with advanced features, such as: 1) Secure Computation, 2) Off-chain Computation, 3) Verifiable Computation, and 4)Support dApps' needs like privacy-preserving data exchange

    A processing element architecture for high-density focal plane analog programmable array processors

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    The architecture of the elementary Processing Element - PE- used in a recently designed 128×128 Focal Plane Analog Programmable Array Processor is presented. The PE architecture contains the required building blocks to implement bifurcated data flow vision algorithms based on the execution of 3 × 3 convolution masks. The vision chip has been implemented in a standard 0.35μm CMOS technology. The main PE related figures are: 180 cells/mm2, 18 MOPS/cell, and 180 μW/cell.Office of Naval Research (USA) N68171-98-C-9004Euopean Union IST-1999-19007Comisión Interministerial de Ciencia y Tecnología TIC1 999-082

    Packet Transactions: High-level Programming for Line-Rate Switches

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    Many algorithms for congestion control, scheduling, network measurement, active queue management, security, and load balancing require custom processing of packets as they traverse the data plane of a network switch. To run at line rate, these data-plane algorithms must be in hardware. With today's switch hardware, algorithms cannot be changed, nor new algorithms installed, after a switch has been built. This paper shows how to program data-plane algorithms in a high-level language and compile those programs into low-level microcode that can run on emerging programmable line-rate switching chipsets. The key challenge is that these algorithms create and modify algorithmic state. The key idea to achieve line-rate programmability for stateful algorithms is the notion of a packet transaction : a sequential code block that is atomic and isolated from other such code blocks. We have developed this idea in Domino, a C-like imperative language to express data-plane algorithms. We show with many examples that Domino provides a convenient and natural way to express sophisticated data-plane algorithms, and show that these algorithms can be run at line rate with modest estimated die-area overhead.Comment: 16 page

    Skyrmion Gas Manipulation for Probabilistic Computing

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    The topologically protected magnetic spin configurations known as skyrmions offer promising applications due to their stability, mobility and localization. In this work, we emphasize how to leverage the thermally driven dynamics of an ensemble of such particles to perform computing tasks. We propose a device employing a skyrmion gas to reshuffle a random signal into an uncorrelated copy of itself. This is demonstrated by modelling the ensemble dynamics in a collective coordinate approach where skyrmion-skyrmion and skyrmion-boundary interactions are accounted for phenomenologically. Our numerical results are used to develop a proof-of-concept for an energy efficient (μW\sim\mu\mathrm{W}) device with a low area imprint (μm2\sim\mu\mathrm{m}^2). Whereas its immediate application to stochastic computing circuit designs will be made apparent, we argue that its basic functionality, reminiscent of an integrate-and-fire neuron, qualifies it as a novel bio-inspired building block.Comment: 41 pages, 20 figure
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