Computer Science and Mathematics Publications

Publications

Memristive Mixed-Signal Neuromorphic Systems: Energy-Efficient Learning at the Circuit-Level

Journal: IEEE Xplore

Neuromorphic computing is a non-von Neumann computer architecture for the post Moore’s law era of computing. Since a main focus of the post Moore’s law era is energy-efficient computing with fewer resources and less area, neuromorphic computing contributes effectively in this research. In this paper we present a...

Memristive Ion Channel-Doped Biomembranes as Synaptic Mimics

Journal: ACS Nano

Solid-state neuromorphic systems based on transistors or memristors have yet to achieve the interconnectivity, performance, and energy efficiency of the brain due to excessive noise, undesirable material properties, and nonbiological switching mechanisms. Here we demonstrate that an alamethicin-doped, synthetic...

Cloud Quantum Computing of an Atomic Nucleus

Journal: Physical Review Letters

We report a quantum simulation of the deuteron binding energy on quantum processors accessed via cloud servers. We use a Hamiltonian from pionless effective field theory at leading order. We design a low-depth version of the unitary coupled-cluster ansatz, use the variational quantum eigensolver algorithm, and compute...

A language and hardware independent approach to quantum–classical computing

Journal: ScienceDirect

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 (...

Superdense Coding over Optical Fiber Links with Complete Bell-State Measurements

Journal: Physical Review Letters

Adopting quantum communication to modern networking requires transmitting quantum information through a fiber-based infrastructure. We report the first demonstration of superdense coding over optical fiber links, taking advantage of a complete Bell-state measurement enabled by time-polarization hyperentanglement,...

Big Effect of Small Nanoparticles: A Shift in Paradigm for Polymer Nanocomposites

Journal: ACS Nano

Polymer nanocomposites (PNCs) are important materials that are widely used in many current technologies and potentially have broader applications in the future due to their excellent property tunability, light weight, and low cost. However, expanding the limits in property enhancement remains a fundamental scientific...

Atomic Defects in Monolayer Titanium Carbide (Ti3C2Tx) MXene

Journal: ACS Nano

The 2D transition metal carbides or nitrides, or MXenes, are emerging as a group of materials showing great promise in lithium ion batteries and supercapacitors. Until now, characterization and properties of single-layer MXenes have been scarcely reported. Here, using scanning transmission electron microscopy, we...

Global adjoint tomography: first-generation model

Journal: Geophysical Journal International

We present the first-generation global tomographic model constructed based on adjoint tomography, an iterative full-waveform inversion technique. Synthetic seismograms were calculated using GPU-accelerated spectral-element simulations of global seismic wave propagation, accommodating effects due to 3-D anelastic crust...

Controllable conversion of quasi-freestanding polymer chains to graphene nanoribbons

Journal: Nature Communications

In the bottom-up synthesis of graphene nanoribbons (GNRs) from self-assembled linear polymer intermediates, surface-assisted cyclodehydrogenations usually take place on catalytic metal surfaces. Here we demonstrate the formation of GNRs from quasi-freestanding polymers assisted by hole injections from a scanning...

A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers

Journal: Neural and Evolutionary Computing

Current Deep Learning approaches have been very successful using convolutional neural networks (CNN) trained on large graphical processing units (GPU)-based computers. Three limitations of this approach are: 1) they are based on a simple layered network topology, i.e., highly connected layers, without intra-layer...

Programming with BIG Data in R: Scaling Analytics from One to Thousands of Nodes

Journal: Big Data Research

We present a tutorial overview showing how one can achieve scalable performance with R. We do so by utilizing several package extensions, including those from the pbdR project. These packages consist of high performance, high-level interfaces to and extensions of MPI, PBLAS, ScaLAPACK, I/O libraries, profiling...

A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers

Journal: IEEE Xplore

Current Deep Learning models use highly optimized convolutional neural networks (CNN) trained on large graphical processing units (GPU)-based computers with a fairly simple layered network topology, i.e., highly connected layers, without intra-layer connections. Complex topologies have been proposed, but are...

Cryogenic Memory Cell Design Based on Small Coupled Arrays of Josephson Junctions

Journal: Superconductor Science and Technology

We demonstrated a paradigm for cryogenic memory operation and presented a specific example of a circuit that consists of three inductively coupled Josephson junctions. We have employed Josephson junction parameter values that are consistent with the current state-of-the-art Josephson junction fabrication capabilities...

Theoretical Study of the Initial Stages of Self-Assembly of a Carboxysome’s Facet

Journal: ACS Nano

Bacterial microcompartments, BMCs,  are organelles that exist within certain type of bacteria and act as nano-factories. Among the different types of known BMCs, the  carboxysome has been studied the most. The carboxysome plays an important role in the light-independent part of the photosynthesis process, where its...

Optimizing End-to-End Big Data Transfers over Terabits Network Infrastructure

Journal: IEEE Transactions on Parallel and Distributed Systems

While future terabit networks hold the promise of significantly improving big-data motion among geographically distributed data centers, significant challenges must be overcome even on today’s 100 gigabit networks to realize end-to-end performance. Multiple bottlenecks exist along the end-to-end path from source to...

Mini-Ckpts: Surviving OS Failures in Persistent Memory

Journal: Proceedings of the 30th ACM International Conference on Supercomputing (ICS) 2016

Concern is growing in the high-performance computing (HPC) community on the reliability of future extreme-scale systems. Current efforts have focused on application fault-tolerance rather than the operating system (OS), despite the fact that recent studies have suggested that failures in OS memory are more likely. The...

Progress in Fast, Accurate Multi-scale Climate Simulations

Journal: Procedia Computer Science

We present a survey of physical and computational techniques that have the potential to contribute to the next generation of high-fidelity, multi-scale climate simulations. Examples of the climate science problems that can be investigated with more depth with these computational improvements include the capture of...

Crystal Structures, Surface Stability, and Water Adsorption Energies of La-Bastnäsite via Density Functional Theory and Experimental Studies

Journal: The Journal of Physical Chemistry C

Bastnäsite is a fluoro-carbonate mineral that is the largest source of rare earth elements (REEs) such as Y, La, and Ce. With increasing demand for REE in many emerging technologies, there is an urgent need for improving the efficiency of ore beneficiation by froth flotation. To design improved flotation agents that...

A hybrid computational strategy to address WGS variant analysis in >5000 samples

Journal: A hybrid computational strategy to address WGS variant analysis in >5000 samples

Background The decreasing costs of sequencing are driving the need for cost effective and real time variant calling of whole genome sequencing data. The scale of these projects are far beyond the capacity of typical computing resources available with most research labs. Other infrastructures like the cloud AWS...

Algorithm-Directed Data Placement in Explicitly Managed Non-Volatile Memory

Journal: ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC)

The emergence of many non-volatile memory (NVM) techniques is poised to revolutionize main memory systems because of the relatively high capacity and low lifetime power consumption of NVM. However, to avoid the typical limitation of NVM as the main memory, NVM is usually combined with DRAM to form a hybrid NVM/DRAM...

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