A Language and Hardware Independent Approach to Quantum-Classical Computing

Heterogeneous high-performance computing (HPC) systems offer novel architectures which accelerate specific workloads through judicious use of specialized coprocessors. A promising architectural approach for future scientific computations is provided by heterogeneous HPC systems integrating quantum processing units (QPUs). To this end, we present XACC (eXtreme-scale ACCelerator) --- a programming model and software framework that enables quantum acceleration within standard or HPC software workflows. XACC follows a coprocessor machine model that is independent of the underlying quantum computing hardware, thereby enabling quantum programs to be defined and executed on a variety of QPUs types through a unified application programming interface. Moreover, XACC defines a polymorphic low-level intermediate representation, and an extensible compiler frontend that enables language independent quantum programming, thus promoting integration and interoperability across the quantum programming landscape. In this work we define the software architecture enabling our hardware and language independent approach, and demonstrate its usefulness across a range of quantum computing models through illustrative examples involving the compilation and execution of gate and annealing-based quantum programs

SIMPEL: Circuit model for photonic spike processing laser neurons

We propose an equivalent circuit model for photonic spike processing laser neurons with an embedded saturable absorber---a simulation model for photonic excitable lasers (SIMPEL). We show that by mapping the laser neuron rate equations into a circuit model, SPICE analysis can be used as an efficient and accurate engine for numerical calculations, capable of generalization to a variety of different laser neuron types found in literature. The development of this model parallels the Hodgkin--Huxley model of neuron biophysics, a circuit framework which brought efficiency, modularity, and generalizability to the study of neural dynamics. We employ the model to study various signal-processing effects such as excitability with excitatory and inhibitory pulses, binary all-or-nothing response, and bistable dynamics.Comment: 16 pages, 7 figure

Overview on the Blockchain-Based Supply Chain Systematics and Their Scalability Tools

Modern IT technologies shaped the shift in economic models with many advantages on cost, optimization, and time to market. This economic shift has increased the need for transparency and traceability in supply chain platforms to achieve trust among partners. Distributed ledger technology (DLT) is proposed to enable supply chains systems with trust requirements. In this paper, we investigate the existing DLT-based supply chain projects to show their technical part and limitations and extract the tools and techniques used to avoid the DLT scalability issue. We then set the requirements for a typical DLT-based supply chain in this context. The analyses are based on the scalability metrics such as computing, data storage, and transaction fees that fit the typical supply chain system. This paper highlights the effects of Blockchain techniques on scalability and their incorporation in supply chains systems. It also presents other existing solutions that can be applied to the supply chain. The investigation shows the necessity of having such tools in supply chains and developing them to achieve an efficient and scalable system. The paper calls for further scalability enhancements throughout introducing new tools and/or reutilize the current ones. Doi: 10.28991/esj-2021-SP1-04 Full Text: PD

Reusable Verification Environment for a RISC-V Vector Accelerator

This paper presents a reusable verification environment developed for the verification of an academic RISC-V based vector accelerator that operates with long vectors. In order to be used across diverse projects, this infrastructure intends to be independent of the interface used for connecting the accelerator to the scalar processor core. We built a verification infrastructure consisting of a Universal Verification Environment (UVM) which is capable of validating the design performing co-simulation of the vector instructions. Moreover, we provided a set of tests and an automated test generation, simulation and error reporting infrastructure. This paper shares our experience on verifying a complex accelerator used in two distinct projects, with different interfaces.This research has received funding from the European High Performance Computing Joint Undertaking (JU) under Framework Partnership Agreement No 800928 (European Processor Initiative) and Specific Grant Agreement No 101036168 (EPI SGA2) and No 956702 (eProcessor) . The JU receives support from the European Union’s Horizon 2020 research and innovation programme and from Croatia, France, Germany, Greece, Italy, Netherlands, Portugal, Spain, Sweden, and Switzerland. The EPI-SGA2 project, PCI2022-132935_N1618737 is also co-funded by MCIN/AEI /10.13039/501100011033 and by the UE NextGenerationEU/PRTRPeer ReviewedPostprint (author's final draft

eViper: A Scalable Platform for Untethered Modular Soft Robots

Soft robots present unique capabilities, but have been limited by the lack of scalable technologies for construction and the complexity of algorithms for efficient control and motion, which depend on soft-body dynamics, high-dimensional actuation patterns, and external/on-board forces. This paper presents scalable methods and platforms to study the impact of weight distribution and actuation patterns on fully untethered modular soft robots. An extendable Vibrating Intelligent Piezo-Electric Robot (eViper), together with an open-source Simulation Framework for Electroactive Robotic Sheet (SFERS) implemented in PyBullet, was developed as a platform to study the sophisticated weight-locomotion interaction. By integrating the power electronics, sensors, actuators, and batteries on-board, the eViper platform enables rapid design iteration and evaluation of different weight distribution and control strategies for the actuator arrays, supporting both physics-based modeling and data-driven modeling via on-board automatic data-acquisition capabilities. We show that SFERS can provide useful guidelines for optimizing the weight distribution and actuation patterns of the eViper to achieve the maximum speed or minimum cost-of-transportation (COT).Comment: 8 pages, 21 figures, accepted by IROS 202

IoT Smart Device for e-Learning Content Sharing on Hybrid Cloud Environment

Centralized e-Learning technology has dominated the learning ecosystem that brings a lot of potential usage on media rich learning materials. However, the centralized architecture has their own constraint to support large number of users for accessing large size of learning contents. On the other hand, Content Delivery Network (CDN) solution which relies on distributed architecture provides an alternative solution to eliminate  bottleneck  access.  Although  CDN  is   an  effective solution, the implementation of technology is expensive and has less impact for student who lives in limited or non-existence internet access in geographical area. In this paper, we introduce an IoT smart device to provide e-Learning access for content sharing on hybrid cloud environment with distributed peer-to- peer communication solution for data synchronization and updates. The IoT smart device acts as an intermediate device between user and cloud services, and provides content sharing solution without fully depending on the cloud server