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Commodity memory interfaces have difficulty in scaling memory capacity to meet the needs of modern multicore and big data systems. DRAM device density and maximum device count are constrained by technology, package, and signal in- tegrity…

Hardware Architecture · Computer Science 2015-05-14 Zehan Cui , Tianyue Lu , Haiyang Pan , Sally A. Mckee , Mingyu Chen

Modern cloud databases present scaling as a binary decision: scale-out by adding nodes or scale-up by increasing per-node resources. This one-dimensional view is limiting because database performance, cost, and coordination overhead emerge…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-05 Shahir Abdullah , Syed Rohit Zaman

Parallelization techniques have become ubiquitous for accelerating inference and training of deep neural networks. Despite this, several operations are still performed in a sequential manner. For instance, the forward and backward passes…

Machine Learning · Computer Science 2023-10-30 Federico Danieli , Miguel Sarabia , Xavier Suau , Pau Rodríguez , Luca Zappella

DRAM is the prevalent main memory technology, but its long access latency can limit the performance of many workloads. Although prior works provide DRAM designs that reduce DRAM access latency, their reduced storage capacities hinder the…

Hardware Architecture · Computer Science 2020-05-27 Haocong Luo , Taha Shahroodi , Hasan Hassan , Minesh Patel , Abdullah Giray Yaglikci , Lois Orosa , Jisung Park , Onur Mutlu

In recent years, data-intensive applications have been increasingly deployed on cloud systems. Such applications utilize significant compute, memory, and I/O resources to process large volumes of data. Optimizing the performance and…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-11-15 Qing Wang , Snigdhaswin Kar , Prabodh Mishra , Caleb Linduff , Ryan Izard , Khayam Anjam , Geddings Barrineau , Junaid Zulfiqar , Kuang-Ching Wang

Work-stealing is a widely used technique for balancing irregular parallel workloads, and most modern runtime systems adopt lock-free work-stealing deques to reduce contention and improve scalability. However, existing algorithms are…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-03-09 Raja Sai Nandhan Yadav Kataru , Danial Davarnia , Ali Jannesari

Large-scale graph processing has drawn great attention in recent years. Most of the modern-day datacenter workloads can be represented in the form of Graph Processing such as MapReduce etc. Consequently, a lot of designs for Domain-Specific…

Hardware Architecture · Computer Science 2022-09-07 Khushal Sethi

We experimentally analyze the computational capability of commercial off-the-shelf (COTS) DRAM chips and the robustness of these capabilities under various timing delays between DRAM commands, data patterns, temperature, and voltage levels.…

RRAM-based multi-core systems improve the energy efficiency and performance of CNNs. Thereby, the distributed parallel execution of convolutional layers causes critical data dependencies that limit the potential speedup. This paper presents…

Hardware Architecture · Computer Science 2023-10-27 Rebecca Pelke , Nils Bosbach , Jose Cubero , Felix Staudigl , Rainer Leupers , Jan Moritz Joseph

Modern computer systems are characterized by deep memory hierarchies, composed of main memory, multiple layers of cache, and other specialized types of memory. In parallel and distributed systems, additional memory layers are added to this…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-07-18 David Walker , Anthony Skjellum

Multi-core architectures feature an intricate hierarchy of cache memories, with multiple levels and sizes. To adequately decompose an application according to the traits of a particular memory hierarchy is a cumbersome task that may be…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-11-20 Hervé Paulino , Nuno Delgado

We have extended the Falkon lightweight task execution framework to make loosely coupled programming on petascale systems a practical and useful programming model. This work studies and measures the performance factors involved in applying…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-17 Ioan Raicu , Zhao Zhang , Mike Wilde , Ian Foster , Pete Beckman , Kamil Iskra , Ben Clifford

OpenCL is a standard for parallel programming of heterogeneous systems. The benefits of a common programming standard are clear; multiple vendors can provide support for application descriptions written according to the standard, thus…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-23 Pekka Jääskeläinen , Carlos Sánchez de La Lama , Erik Schnetter , Kalle Raiskila , Jarmo Takala , Heikki Berg

This paper summarizes the idea of Subarray-Level Parallelism (SALP) in DRAM, which was published in ISCA 2012, and examines the work's significance and future potential. Modern DRAMs have multiple banks to serve multiple memory requests in…

Hardware Architecture · Computer Science 2018-05-08 Yoongu Kim , Vivek Seshadri , Donghyuk Lee , Jamie Liu , Onur Mutlu

Distinct HEP workflows have distinct I/O needs; while ROOT I/O excels at serializing complex C++ objects common to reconstruction, analysis workflows typically have simpler objects and can sustain higher event rates. To meet these…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-08-26 Brian Bockelman , Zhe Zhang , Oksana Shadura

To process a large volume of data, modern data management systems use a collection of machines connected through a network. This paper looks into the feasibility of scaling up such a shared-nothing system while processing a compute- and…

Databases · Computer Science 2018-04-26 Abhirup Chakraborty

Computer-use agents increasingly operate inside live personal workspaces, where their actions can modify files, applications, GUI state, credentials, and authenticated sessions. This creates a tension between safety and quality: agents need…

Operating Systems · Computer Science 2026-05-19 Yutong Huang , Vikranth Srivatsa , Alex Asch , Hansin Tushar Patwa , Yiying Zhang

Radiative transfer modelling is part of many astrophysical simulations and is used to make synthetic observations and to assist analysis of observations. We concentrate on the modelling of the radio lines emitted by the interstellar medium.…

Instrumentation and Methods for Astrophysics · Physics 2021-01-04 M. Juvela

Modern information technology services largely depend on cloud infrastructures to provide their services. These cloud infrastructures are built on top of datacenter networks (DCNs) constructed with high-speed links, fast switching gear, and…

Machine Learning · Computer Science 2018-09-25 Ting-Yu Mu , Ala Al-Fuqaha , Khaled Shuaib , Farag M. Sallabi , Junaid Qadir

The fast marching method is well-known for its worst-case optimal computational complexity in solving the Eikonal equation, and has been employed in numerous scientific and engineering fields. However, it has barely benefited from…

Computational Physics · Physics 2018-11-02 Jianming Yang