20 papers · ranked by Valyu relevance
Jorge F Mejías, Xiao-Jing Wang, Tatiana Pasternak, Tirin Moore
Neural activity underlying working memory is not a local phenomenon but distributed across multiple brain regions. To elucidate the circuit mechanism of such distributed activity, we developed an anatomically constrained computational model of large-scale macaque cortex. We found that mnemonic internal states may…
Anil Yelam
Memory disaggregation addresses memory imbalance in a cluster by decoupling CPU and memory allocations of applications while also increasing the effective memory capacity for (memory-intensive) applications beyond the local memory limit imposed by traditional fixed-capacity servers. As the network speeds in the…
Mengli Feng, Abhirup Bandyopadhyay, Jorge F. Mejias
Working memory is a fundamental cognitive function which allows to transiently store and manipulate relevant information in memory. While it has been traditionally linked to activity in specific prefrontal cortical areas, recent electrophysiological and imaging evidence has shown co-occurrent activities in different…
Xingyu Ding, Sean Froudist-Walsh, Jorge Jaramillo, Junjie Jiang + 1 more
Recent advances in connectome and neurophysiology make it possible to probe whole-brain mechanisms of cognition and behavior. We developed a large-scale model of the mouse multiregional brain for a cardinal cognitive function called working memory, the brain’s ability to internally hold and process information without…
Kevin Garner, Polykarpos Thomadakis, Nikos Chrisochoides
This paper presents a distributed memory method for anisotropic mesh adaptation that is designed to avoid the use of collective communication and global synchronization techniques. In the presented method, meshing functionality is separated from performance aspects by utilizing a separate entity for each - a multicore…
Jaewan Hong, Marcos K. Aguilera, Emmanuel Amaro, Vincent Liu + 2 more
'Aurojit Panda' 'Ion Stoica'] Disaggregated memory is an upcoming data center technology that will allow nodes (servers) to share data efficiently. Sharing data creates a debate on the level of cache coherence the system should provide.While current proposals aim to provide coherence for all or parts of the…
Amit Puri, John Jose, Tamarapalli Venkatesh
—Memory disaggregation is being considered as a strong alternative to traditional architecture to deal with the memory under-utilization in data centers. Disaggregated memory can adapt to dynamically changing memory requirements for the data center applications like data analytics, big data, etc., that require…
Christina Giannoula, Kailong Huang, Jonathan Tang, Nectarios Koziris + 3 more
'Georgios Goumas' 'Zeshan Chishti' 'Nandita Vijaykumar'] Resource disaggregation offers a cost effective solution to resource scaling, utilization, and failure-handling in data centers by physically separating hardware devices in a server. Servers are architected as pools of processor, memory, and storage devices…
Derek J. Huffman, Ruijia Guan
Episodic memory is a core function that allows us to remember the events of our lives. Given that many events in our life contain overlapping elements (e.g., similar people and places), it is critical to understand how well we can remember the specific events of our lives vs. how susceptible we are to interference…
Julia Steinberg, Haim Sompolinsky
A long standing challenge in biological and artificial intelligence is to understand how new knowledge can be constructed from known building blocks in a way that is amenable for computation by neuronal circuits. Here we focus on the task of storage and recall of structured knowledge in long-term memory. Specifically…
Denis Hünich, Andreas Knüpfer, Daniele D’Agostino
The Partitioned Global Address Space (PGAS) library DASH provides C++ container classes for distributed N-dimensional structured grids. This article presents enhancements on top of the DASH library to support stencil operations and halo areas to conveniently and efficiently parallelize structured grids. The…
Joel C. Wallenberg, Salsabila Nadhif Fadhilah, Taylor D. Hinton, Tom V. Smulders + 2 more
This study builds on work on language processing and information theory which suggests that informationally uniform, or smoother, sequences are easier to process than ones in which information arrives in clumps. Because episodic memory is a form of memory in which information is encoded within its surrounding context…
Christina Giannoula, Kailong Huang, Jonathan Tang, Nectarios Koziris + 3 more
'Georgios Goumas' 'Zeshan Chishti' 'Nandita Vijaykumar'] | | | Christina Giannoula§† | Kailong Huang§ | Jonathan Tang§ | | --- | --- | --- | --- | --- | | s | Nectarios Koziris† | Georgios Goumas† | Zeshan Chishti‡ | Nandita Vijaykumar§ | | | §University of Toronto | | †National Technical University of Athens | ‡ Intel…
Saugata Ghose
The first years of the 2000s led to an inflection point in computer architectures: while the number of available transistors on a chip continued to grow, crucial transistor scaling properties started to break down and result in increasing power consumption, while aggressive single-core performance optimizations were…
Bohan Li, Xin He, Junyang Yu, Guanghui Wang + 4 more
'Shunjie Pan' 'Hangyu Gu' 'Joanna Rosak-Szyrocka'] The rise of the Internet of Things (IoT) and Industry 2.0 has spurred a growing need for extensive data computing, and Spark emerged as a promising Big Data platform, attributed to its distributed in-memory computing capabilities. However, practical heavy workloads…
Andrei-Alin Corodescu, Nikolay Nikolov, Akif Quddus Khan, Ahmet Soylu + 4 more
'Ahmet Soylu' 'Mihhail Matskin' 'Amir H. Payberah' 'Dumitru Roman' 'Haipeng Dai'] The emergence of the edge computing paradigm has shifted data processing from centralised infrastructures to heterogeneous and geographically distributed infrastructures. Therefore, data processing solutions must consider data locality to…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Jinho Park, Kwangsue Chung, Sergio Toral Marín
Various edge collaboration schemes that rely on reinforcement learning (RL) have been proposed to improve the quality of experience (QoE). Deep RL (DRL) maximizes cumulative rewards through large-scale exploration and exploitation. However, the existing DRL schemes do not consider the temporal states using a fully…
Authors not listed
Computing electrostatic interactions remains the bottleneck of molecular dynamics (MD) simulations despite more than a century of effort in developing methods to accelerate the calculation. Previously we have developed the Spherical Grid and Treecode (SGT) and Gauss-Legendre-Spherical-t (GLST) algorithms for…
Authors not listed
Modeling multimetallic systems efficiently enables faster prediction of desirable chemical properties and design of new materials. This work describes an initial implementation for performing multireference wave function method localized active space self-consistent field (LASSCF) calculations through the use of…