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Krishnamoorthy, Sriram

Publications and source records attributed to Krishnamoorthy, Sriram.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Photoluminescence mapping of laser-damaged β-Ga 2 O 3

Here, photoluminescence (PL) mapping was utilized to investigate damage in β-Ga 2 O 3 epilayers induced by 1064 nm laser pulses. The intensity and position of the intrinsic UV band were determined and plotted as a false-color image. Two types of damage were identified: circular damage and damage cracks. Circular damage shows lower UV PL intensity than the surrounding material with color centers in a “halo” around the damaged region. Damage cracks are aligned with the a and c axes and show higher PL intensity than undamaged material. Defects in the as-grown material were revealed by shifts in the UV band energy.

36 MATERIALS SCIENCE↗
DOE OSTI2023

TAMM: Tensor algebra for many-body methods

Tensor algebra operations such as contractions in computational chemistry consume a significant fraction of the computing time on large-scale computing platforms. The widespread use of tensor contractions between large multi-dimensional tensors in describing electronic structure theory has motivated the development of multiple tensor algebra frameworks targeting heterogeneous computing platforms. In this paper, we present Tensor Algebra for Many-body Methods (TAMM), a framework for productive and performance-portable development of scalable computational chemistry methods. TAMM decouples the specification of the computation from the execution of these operations on available high-performance computing systems. With this design choice, the scientific application developers (domain scientists) can focus on the algorithmic requirements using the tensor algebra interface provided by TAMM, whereas high-performance computing developers can direct their attention to various optimizations on the underlying constructs, such as efficient data distribution, optimized scheduling algorithms, and efficient use of intra-node resources (e.g., graphics processing units). The modular structure of TAMM allows it to support different hardware architectures and incorporate new algorithmic advances. We describe the TAMM framework and our approach to the sustainable development of scalable ground- and excited-state electronic structure methods. We present case studies highlighting the ease of use, including the performance and productivity gains compared to other frameworks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

ExaChem/exachem

Open Source Exascale Computational Chemistry Software

Panyala, Ajay↗
DOE OSTI2023

QASMBench: A Low-Level Quantum Benchmark Suite for NISQ Evaluation and Simulation

The rapid development of quantum computing (QC) in the NISQ era urgently demands a low-level benchmark suite and insightful evaluation metrics for characterizing the properties of prototype NISQ devices, the efficiency of QC programming compilers, schedulers and assemblers, and the capability of quantum system simulators in a classical computer. In this work, we fill this gap by proposing a low-level, easy-to-use benchmark suite called QASMBench based on the OpenQASM assembly representation. It consolidates commonly used quantum routines and kernels from a variety of domains including chemistry, simulation, linear algebra, searching, optimization, arithmetic, machine learning, fault tolerance, cryptography, and so on, trading-off between generality and usability. To analyze these kernels in terms of NISQ device execution, in addition to circuit width and depth, we propose four circuit metrics including gate density, retention lifespan, measurement density, and entanglement variance, to extract more insights about the execution efficiency, the susceptibility to NISQ error, and the potential gain from machine-specific optimizations. Applications in QASMBench can be launched and verified on several NISQ platforms, including IBM-Q, Rigetti, IonQ and Quantinuum. For evaluation, we measure the execution fidelity of a subset of QASMBench applications on 12 IBM-Q machines through density matrix state tomography, comprising 25K circuit evaluations. In addition we also compare the fidelity of executions among the IBM-Q machines, the IonQ QPU and the Rigetti Aspen M-1 system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Enhancing the electron mobility in Si-doped (010) β-Ga 2 O 3 films with low-temperature buffer layers

We demonstrate a new substrate cleaning and buffer growth scheme in β-Ga 2 O 3 epitaxial thin films using metal–organic vapor phase epitaxy (MOVPE). For the channel structure, a low-temperature (LT, 600 °C) un-doped Ga 2 O 3 buffer was grown, followed by a transition layer to a high-temperature (HT, 810 °C) Si-doped Ga 2 O 3 channel layers without growth interruption. The (010) Ga 2 O 3 Fe-doped substrate cleaning uses solvent cleaning, followed by additional hydrofluoric acid (49% in water) treatment for 30 min before the epilayer growth. This step is shown to compensate the parasitic Si channel at the epilayer–substrate interface that originates from the substrate polishing process or contamination from the ambient. From secondary ion mass spectroscopy (SIMS) analysis, the Si peak atomic density at the substrate interface is found to be several times lower than the Fe atomic density in the substrate—indicating full compensation. The elimination of the parasitic electron channel at the epi–substrate interface was also verified by electrical (capacitance–voltage profiling) measurements. In the LT-grown (600 °C) buffer layers, it is seen that the Fe forward decay tail from the substrate is very sharp, with a decay rate of ∼9 nm/dec. X-ray off-axis rocking curve ω-scans show very narrow full width at half maximum (FWHM) values, similar to the as-received substrates. These channels show record high electron mobility in the range of 196–85 cm 2 /V⋅s in unintentionally doped and Si-doped films in the doping range of 2 × 10 16 –1 × 10 20 cm −3 . Si delta-doped channels were also grown utilizing this substrate cleaning and the hybrid LT buffers. Record high electron Hall mobility of 110 cm 2 /V⋅s was measured for sheet charge density of 9.2 × 10 12 cm −2 . This substrate cleaning, combined with the LT buffer scheme, shows the potential of designing Si-doped β-Ga 2 O 3 channels with exceptional transport properties for high-performance Ga 2 O 3 -based electron devices.

Bhattacharyya, Arkka↗
DOE OSTI2022

Efficient Hierarchical State Vector Simulation of Quantum Circuits via Acyclic Graph Partitioning

Early but promising results in quantum computing have been enabled by the concurrent development of quantum algorithms, devices, and materials. Classical simulation of quantum programs has enabled the design and analysis of algorithms and implementation strategies targeting current and anticipated quantum device architectures. In this paper, we present a graph-based approach to achieve efficient quantum circuit simulation. Our approach involves partitioning the graph representation of a given quantum circuit into sub-graphs/circuits that exhibit better data locality. Simulation of each sub-circuit is organized hierarchically, with the iterative construction and simulation of smaller state vectors, improving overall performance. Also, this partitioning reduces the number of passes through data, improving the total computation time. We present three partitioning strategies and observe that acyclic graph partitioning typically results in the best time-to-solution. In contrast, other strategies reduce the partitioning time at the expense of potentially increased simulation times. Experimental evaluation demonstrates the effectiveness of our approach.

Fang, Bo↗
DOE OSTI2022

spec-org/gfcc

Green's Function Coupled Cluster Library SPEC GFCC library enables calculations for spectral functions and binding energies of molecular systems using highly scalable implementation of the Green's function coupled cluster (GFCC) approach

Panyala, Ajay↗
DOE OSTI2022

Optimized Quantum Phase Estimation for Simulating Electronic States in Various Energy Regimes

While quantum algorithms for simulation exhibit better asymptotic scaling than their classical counterparts, they currently cannot be implemented on real-world devices. Instead, chemists and computer scientists rely on costly classical simulations of these quantum algorithms. In particular, the quantum phase estimation (QPE) algorithm is among several approaches that have attracted much attention in recent years for its genuine quantum character. However, it is memory-intensive to simulate and intractable for moderate system sizes. Herein, this paper discusses the performance and applicability of QPESIM, a new simulation of the QPE algorithm designed to take advantage of modest computational resources. In particular, we demonstrate the versatility of QPESIM in simulating various electronic states by examining the ground and core-level states of H 2 O. For these states, we also discuss the effect of the active-space size on the quality of the calculated energies. For the high-energy core-level states, we demonstrate that new QPE simulations for active spaces defined by 15 active orbitals significantly reduce the errors in core-level excitation energies compared to earlier QPE simulations using smaller active spaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

COMET: A Domain-Specific Compilation of High-Performance Computational Chemistry

The computational power increases over the past decades have greatly enhanced the ability to simulate chemical reactions and understand ever more complex transformations. Tensor contractions are the fundamental computational building block of these simulations. These simulations have often been tied to one platform and restricted in generality by the interface provided to the user. The expanding prevalence of accelerators and researcher demands necessitate a more general approach which is not tied to specific hardware or requires contortion of algorithms to specific hardware platforms. In this paper we present COMET, a domain-specific programming language and compiler infrastructure for tensor contractions targeting heterogeneous accelerators. We present a system of progressive lowering through multiple layers of abstraction and optimization that achieves up to 1.98×speedup for 30 tensor contractions commonly used in computational chemistry and beyond.

Mutlu, Erdal↗
DOE OSTI2021

SV-Sim: Scalable PGAS-based State Vector Simulation of Quantum Circuits

High-performance quantum circuit simulation in a classic HPC is still imperative in the NISQ era. Observing that the major obstacle of scalable state-vector quantum simulation arises from the massively fine-grained irregular data-exchange with remote nodes, in this paper we present SV-Sim to apply the emerging PGAS-based communication models (i.e., direct peer access for intra-node CPUs/GPUs and SHMEM for inter-node CPU/GPU clusters) for efficient scalable quantum circuit simulation. Through an orchestrated device functional pointer design, SV-Sim is able to abstract the quantum gate sets across various heterogeneous backends, including IBM/Intel/AMD CPUs, NVIDIA /AMD GPUs, and Intel MIC, in a unified framework, but still asserting outstanding performance and tractable interface to higher-level quantum programming environments, such as IBM Qiskit, Microsoft Q\# and Google Cirq. Circumventing the disability of polymorphism in GPUs and leveraging the device-initiated one-sided communication, SV-Sim can process dynamically synthesized quantum circuit in a single GPU/CPU kernel without the need of expensive JIT or runtime branching, significantly improving the performance and simplifying the programming complexity for the emerging variational quantum algorithms. Evaluations on NVIDIA A100-DGX-1, V100-DGX-2, AMD MI100, ALCF Theta, and OLCF Summit HPCs show that SV-Sim can delivery scalable performance on various state-of-the-art HPC platforms, offering a useful tool for quantum algorithm validation and verification.

Li, Ang↗
DOE OSTI2021

Characterizing Impacts of Storage Faults on HPC Applications: A methodology and insights

In recent years, the increasing complexity in scientific simulations and emerging demands for training heavy artificial intelligence models require massive and fast data accesses, which urges high-performance computing (HPC) platforms to equip with more advanced storage infrastructures such as solid-state disks (SSDs). While SSDs offer high-performance I/O, it remains unclear about the reliability challenges faced by the HPC applications under the SSD-related failures, in particular, failures resulting in data corruptions. The goal of this paper is to understand the impact of SSD-related data corruptions on the behaviors of complex HPC applications. To this end, we propose FFIS, a FUSE-based fault injection framework that systematically introduces storage faults into the application layer to model the errors originated from SSDs. FFIS is able to plant different I/O related faults into the data returned from underlying file systems, which also enables the investigation on the error resilience characteristics of the scientific file format for the first time. We demonstrate the use of FFIS with three representative real HPC applications, show how each application reacts to the data corruptions, and provide insights on the error resilience of the widely-adopted HDF5 file format for the HPC applications.

Fang, Bo↗
DOE OSTI2021

NWQ-sim

NWQSim is a quantum circuit simulation environment developed at PNNL. It currently includes two major components: a state-vector simulator (SV-Sim) and a density matrix simulator (DM-Sim) and we may add more components, such as a Clifford simulator, in the future effort. NWQSim has two language interface: C/C++ and Python. It supports Q#/QDK frontend through QIR and QIR-runtime. It supports Qiskit and Cirq frontends through OpenQASM. NWQSim runs on several backends: Intel-CPU, Intel-Xeon-Phi, AMD-CPU, AMD-GPU, NVIDIA-GPU, and IBM-CPU. It supports three modes: (1) single processor, such as a single CPU (with and without AVX2 and AVX512 acceleration), a single NVIDIA GPU or a single AMD GPU; (2) single-node-multi-processors, such as multi-CPUs/Xeon-Phis, multi-NVIDA/AMD GPUs; (3) multi-nodes, such as a CPU cluster, a Xeon-Phi cluster (e.g., ANL Theta, NERSC Cori), an NVIDIA cluster (e.g., ORNL Summit, NERSC Perlmutter).

Li, Ang↗
DOE OSTI2021

pnnl/DM-Sim

DM-Sim: Quantum Simulator on GPU Cluster using Density Matrix: a new simulation approach that significantly reduces communication overhead.

Li, Ang↗
DOE OSTI2021

Thermal Conductivity of β-Phase Ga 2 O 3 and (Al x Ga 1– x ) 2 O 3 Heteroepitaxial Thin Films

Heteroepitaxy of β-phase gallium oxide (β-Ga 2 O 3 ) thin films on foreign substrates shows promise for the development of next-generation deep ultraviolet solar blind photodetectors and power electronic devices. In this work, the influences of the film thickness and crystallinity on the thermal conductivity of ($\bar{2}01$)-oriented β-Ga 2 O 3 heteroepitaxial thin films were investigated. Unintentionally doped β-Ga 2 O 3 thin films were grown on c-plane sapphire substrates with off-axis angles of 0° and 6° toward $\langle$$11\bar{2}0$$\rangle$ via metal–organic vapor phase epitaxy (MOVPE) and low-pressure chemical vapor deposition. The surface morphology and crystal quality of the β-Ga 2 O 3 thin films were characterized using scanning electron microscopy, X-ray diffraction, and Raman spectroscopy. The thermal conductivities of the β-Ga 2 O 3 films were measured via time-domain thermoreflectance. The interface quality was studied using scanning transmission electron microscopy. The measured thermal conductivities of the submicron-thick β-Ga 2 O 3 thin films were relatively low as compared to the intrinsic bulk value. The measured thin film thermal conductivities were compared with the Debye–Callaway model incorporating phononic parameters derived from first-principles calculations. The comparison suggests that the reduction in the thin film thermal conductivity can be partially attributed to the enhanced phonon-boundary scattering when the film thickness decreases. They were found to be a strong function of not only the layer thickness but also the film quality, resulting from growth on substrates with different offcut angles. Growth of β-Ga 2 O 3 films on 6° offcut sapphire substrates was found to result in higher crystallinity and thermal conductivity than films grown on on-axis c-plane sapphire. However, the β-Ga 2 O 3 films grown on 6° offcut sapphire exhibit a lower thermal boundary conductance at the β-Ga 2 O 3 /sapphire heterointerface. In addition, the thermal conductivity of MOVPE-grown ($\bar{2}01$)-oriented β-(Al x Ga 1–x ) 2 O 3 thin films with Al compositions ranging from 2% to 43% was characterized. Because of phonon-alloy disorder scattering, the β-(Al x Ga 1–x ) 2 O 3 films exhibit lower thermal conductivities (2.8–4.7 W/m∙K) than the β-Ga 2 O 3 thin films. The dominance of the alloy disorder scattering in β-(Al x Ga 1–x ) 2 O 3 is further evidenced by the weak temperature dependence of the thermal conductivity. This work provides fundamental insight into the physical interactions that govern phonon transport within heteroepitaxially grown β-phase Ga 2 O 3 and (Al x Ga 1–x ) 2 O 3 thin films and lays the groundwork for the thermal modeling and design of β-Ga 2 O 3 electronic and optoelectronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

GFCCLib: Scalable and efficient coupled-cluster Green's function library for accurately tackling many-body electronic structure problems

Coupled-cluster Green’s function (GFCC) calculation has drawn much attention in the recent years for targeting the molecular and material electronic structure problems from a many-body perspective in a systematically improvable way. However, GFCC calculations on scientific computing clusters usually suffer from expensive higher di- mensional tensor contractions in the complex space, expensive inter-process communi- cation, and severe load imbalance, which limits it’s routine use for tackling electronic structure problems. Here we present a numerical library prototype that is specifically designed for large-scale GFCC calculations. The design of the library is focused on a systematically optimal computing strategy to improve its scalability and efficiency. The performance of the library is demonstrated by the relevant profiling analysis of running GFCC calculations on remote giant computing clusters. The capability of the library is highlighted by computing a wide near valence band of a fullerene C60 molecule for the first time at the GFCCSD level that shows excellent agreement with the experimental spectrum.

Peng, Bo↗
DOE OSTI2021

AEDAM: Whole Program Adaptive Error Detection and Mitigation (Final Report)

The overall goals of the AEDAM project were to fundamentally transform software transient-error detection through the design of configurable specialized detectors, quantitative characterization of hardware resilience and software vulnerabilities, and composition of the specialized detectors to most efficiently protect the whole program. Within this scope, UT Austin's research contribution related to enabling and studying the composition of detectors and possible different hardware errors, specifically: (1) developed the Hamartia open-source error injection framework that is designed to make composition studies simple, and (2) develop the methodology and demonstrate the potential benefits of error detector composition.

97 MATHEMATICS AND COMPUTING↗