20 papers · ranked by Valyu relevance
Paul Melo e Castro, Vatche Isahagian, Vinod Muthusamy, Aleksander Slominski
'Aleksander Slominski'] In recent years, there has been a surge in the adoption of serverless computing due to the ease of deployment, attractive pay-per-use pricing, and transparent horizontal auto-scaling. At the same time, infrastructure advancements such as the emergence of 5G networks and the explosion of devices…
A. A. Periola, A. A. Alonge, K. A. Ogudo
Computing platforms have a high water footprint that poses threat to biodiversity preservation. The high water footprint reduces water availability for habitat preservation. Hence, approaches that reduce the water footprint are needful. The presented research proposes an approach that reduces the need for water in…
Shania Rehman, Muhammad Farooq Khan, Hee-Dong Kim, Sungho Kim
Algorithms for intelligent drone flights based on sensor fusion are usually implemented using conventional digital computing platforms. However, alternative energy-efficient computing platforms are required for robust flight control in a variety of environments to reduce the burden on both the battery and computing…
Veronica K. Krasecki, Abhishek Sharma, Andrew C. Cavell, Christopher Forman + 10 more
Noise in a Hybrid Classical-Molecular Computer to Solve Combinatorial Optimization Problems Authors: ['Veronica\nK. Krasecki' 'Abhishek Sharma' 'Andrew C. Cavell' 'Christopher Forman' 'Si Yue Guo' 'Evan Thomas Jensen' 'Mackinsey A. Smith' 'Rachel Czerwinski' 'Pascal Friederich' 'Riley J. Hickman' 'Nathan Gianneschi'…
Rong Zhao, Zheyu Yang, Hao Zheng, Yujie Wu + 16 more
'Zhenzhi Wu' 'Lukai Li' 'Feng Chen' 'Seng Song' 'Jun Zhu' 'Wenli Zhang' 'Haoyu Huang' 'Mingkun Xu' 'Kaifeng Sheng' 'Qianbo Yin' 'Jing Pei' 'Guoqi Li' 'Youhui Zhang' 'Mingguo Zhao' 'Luping Shi'] There is a growing trend to design hybrid neural networks (HNNs) by combining spiking neural networks and artificial neural…
Konstantinos Rallis, Ioannis Liliopoulos, Georgios D. Varsamis, Evangelos Tsipas + 3 more
The connection and eventual integration of High-Performance Computing (HPC) with Quantum Computing (QC) represents a transformative advancement in computational technology, promising significant enhancements in solving complex, previously intractable problems. This manuscript provides a comprehensive overview of the…
Anderson Avila, Helida Santos, Anderson Cruz, Samuel Xavier-de-Souza + 5 more
'Giancarlo Lucca' 'Bruno Moura' 'Adenauer Yamin' 'Renata Reiser' 'Xi Chen'] This paper presents the HybriD-GM model conception, from modeling to consolidation. The D-GM environment is also extended, providing efficient parallel executions for quantum computing simulations, targeted to hybrid architectures considering…
Philip Döbler, Manpreet Singh Jattana
Quantum computers use quantum mechanical phenomena to perform conventionally intractable calculations for specific problems. Despite being universal machines, quantum computers are not expected to replace classical computers, but rather, to complement them and form hybrid systems. This makes integrating quantum…
David S. Cerutti, Rafal Wiewiora, Simon Boothroyd, Woody Sherman
The Structure and TOpology Replica Molecular Mechanics (STORMM) code is a next-generation molecular simulation engine and associated libraries optimized for performance on fast, multicore central processor units (CPUs) and graphics processing units (GPUs) with independent memory and tens of thousands of threads. STORMM…
Bayo Lau, Prashant S. Emani, Jackson Chapman, Lijing Yao + 5 more
While many quantum computing (QC) methods promise theoretical advantages over classical counterparts, quantum hardware remains limited. Exploiting near-term QC in computer-aided drug design (CADD) thus requires judicious partitioning between classical and quantum calculations. We present HypaCADD, a hybrid…
Authors not listed
We describe a collaborative research project spanning the disciplines of quantum hardware, quantum algorithms, conventional computational chemistry, synthetic medicinal chemistry and life sciences. Our project seeks to demonstrate an impact of quantum computing on human health. It is one of several funded by Wellcome…
Sarita Simaiya, Umesh Kumar Lilhore, Yogesh Kumar Sharma, K. B. V. Brahma Rao + 4 more
'K. B. V. Brahma Rao' 'V. V. R. Maheswara Rao' 'Anupam Baliyan' 'Anchit Bijalwan' 'Roobaea Alroobaea'] Virtual machine (VM) integration methods have effectively proven an optimized load balancing in cloud data centers. The main challenge with VM integration methods is the trade-off among cost effectiveness, quality of…
Muhammad Saad, Rabia Noor Enam, Rehan Qureshi
As the volume and velocity of Big Data continue to grow, traditional cloud computing approaches struggle to meet the demands of real-time processing and low latency. Fog computing, with its distributed network of edge devices, emerges as a compelling solution. However, efficient task scheduling in fog computing remains…
José Pinto, Mykaella Mestre, Rafael S. Costa, Gerald Striedner + 1 more
Numerous studies have reported the use of hybrid semiparametric systems that combine shallow neural networks with mechanistic models for bioprocess modeling. Here we revisit the general bioreactor hybrid modeling problem and introduce some of the most recent deep learning techniques. The single layer networks were…
Atefe Darabi, Zheming An, Muhammad Ali Al-Radhawi, William Cho + 2 more
This work explores the integration of machine learning (ML) and mechanistic models (MM). While ML has demonstrated remarkable success in data-driven modeling across engineering, biology, and other scientific fields, MM remain essential for their interpretability and capacity to extrapolate beyond observed conditions…
Madushanka Manathunga, Hasan Metin Aktulga, Andreas W. Goetz, Kenneth M. Merz + 1 more
We have ported and optimized the GPU accelerated QUICK and AMBER based ab initio QM/MM implementation on AMD GPUs. This encompasses the entire Fock matrix build and force calculation in QUICK including one-electron integrals, two-electron repulsion integrals, exchange-correlation quadrature, and linear algebra…
Carlos Martínez, Facundo Rocha Calvette, Marielle Péré, Mauricio Barrientos + 1 more
A hybrid model combines a mechanistic model, described by ordinary differential equations, with a data-driven component, such as neural networks. This strategy leverages both the physical knowledge of the system and the predictive power of machine learning methods, and it has been applied to a variety of bioprocesses.…
Weitang Li, Zhi Yin, Xiaoran Li, Dongqiang Ma + 8 more
Quantum computing, with its superior computational capabilities compared to classical approaches, holds the potential to revolutionize numerous scientific domains, including pharmaceuticals. However, the application of quantum computing for drug discovery has primarily been limited to proof-of-concept studies, which…
Jiasheng Hu, Philip A. Bernstein, Jialin Li, Qizhen Zhang
Improving the performance and reducing the cost of cloud data systems is increasingly challenging. Data processing units (DPUs) are a promising solution, but utilizing them for data processing needs characterizing the new hardware and recognizing their capabilities and constraints. We hence propose DPDPU, a platform…
Authors not listed
The era of exascale computing presents both exciting opportunities and unique challenges for quantum mechanical simulations. While the transition from petaflops to exascale computing has been marked by a steady increase in computational power, the shift towards heterogeneous architectures, particularly the dominant…