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Near-data accelerators (NDAs) that are integrated with main memory have the potential for significant power and performance benefits. Fully realizing these benefits requires the large available memory capacity to be shared between the host…

Hardware Architecture · Computer Science 2020-12-02 Benjamin Y. Cho , Yongkee Kwon , Sangkug Lym , Mattan Erez

Battery-less technology evolved to replace battery usage in space, deep mines, and other environments to reduce cost and pollution. Non-volatile memory (NVM) based processors were explored for saving the system state during a power failure.…

Hardware Architecture · Computer Science 2023-05-18 SatyaJaswanth Badri , Mukesh Saini , Neeraj Goel

Processing-using-DRAM (PUD) architectures impose a restrictive data layout and alignment for their operands, where source and destination operands (i) must reside in the same DRAM subarray (i.e., a group of DRAM rows sharing the same row…

Hardware Architecture · Computer Science 2024-03-08 Geraldo F. Oliveira , Emanuele G. Esposito , Juan Gómez-Luna , Onur Mutlu

Near-data processing (NDP) refers to augmenting memory or storage with processing power. Despite its potential for acceleration computing and reducing power requirements, only limited progress has been made in popularizing NDP for various…

Hardware Architecture · Computer Science 2017-05-01 Hyeokjun Choe , Seil Lee , Hyunha Nam , Seongsik Park , Seijoon Kim , Eui-Young Chung , Sungroh Yoon

Remote direct memory access (RDMA) allows a machine to directly read from and write to the memory of remote machine, enabling high-throughput, low-latency data transfer. Ensuring correctness of RDMA programs has only recently become…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-01-28 Guillaume Ambal , Max Stupple , Brijesh Dongol , Azalea Raad

Sparse code multiple access (SCMA) is a promising technique for future machine type communication systems due to its superior spectral efficiency and capability for supporting massive connectivity. This paper proposes a novel class of…

Information Theory · Computer Science 2025-01-29 Haibo Liu , Qu Luo , Zilong Liu , Shan Luo , Pei Xiao , Xiaojun Yuan

Deep Neural Networks (DNNs) have transformed the field of machine learning and are widely deployed in many applications involving image, video, speech and natural language processing. The increasing compute demands of DNNs have been widely…

Machine Learning · Computer Science 2021-08-17 Sourjya Roy , Mustafa Ali , Anand Raghunathan

Modern multi-socket architectures offer a single virtual address space, but physically divide main-memory across multiple regions, where each region is attached to a CPU and its cores. While this simplifies the usage, developers must be…

Databases · Computer Science 2026-02-06 Felix Schuhknecht , Nick Rassau

Space-Division Multiple Access (SDMA) utilizes linear precoding to separate users in the spatial domain and relies on fully treating any residual multi-user interference as noise. Non-Orthogonal Multiple Access (NOMA) uses linearly precoded…

Information Theory · Computer Science 2018-11-22 Yijie Mao , Bruno Clerckx , Victor O. K. Li

In modern containerized cloud environments, the adoption of RDMA (Remote Direct Memory Access) has expanded to reduce CPU overhead and enable high-performance data exchange. Achieving this requires strong performance isolation to ensure…

Cryptography and Security · Computer Science 2025-10-15 Gunwoo Kim , Taejune Park , Jinwoo Kim

As the High Performance Computing world moves towards the Exa-Scale era, huge amounts of data should be analyzed, manipulated and stored. In the traditional storage/memory hierarchy, each compute node retains its data objects in its local…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-09-07 Yehonatan Fridman , Yaniv Snir , Matan Rusanovsky , Kfir Zvi , Harel Levin , Danny Hendler , Hagit Attiya , Gal Oren

Memory-augmented neural networks (MANNs) provide better inference performance in many tasks with the help of an external memory. The recently developed differentiable neural computer (DNC) is a MANN that has been shown to outperform in…

Hardware Architecture · Computer Science 2022-02-16 Yaoyu Tao , Zhengya Zhang

Conventional multiply-accumulate (MAC) operations have long dominated computation time for deep neural networks (DNNs), espcially convolutional neural networks (CNNs). Recently, product quantization (PQ) has been applied to these workloads,…

Hardware Architecture · Computer Science 2024-04-01 Ahmed F. AbouElhamayed , Angela Cui , Javier Fernandez-Marques , Nicholas D. Lane , Mohamed S. Abdelfattah

Processing-in-memory (PIM) has emerged as a promising solution for accelerating memory-intensive workloads as they provide high memory bandwidth to the processing units. This approach has drawn attention not only from the academic community…

Hardware Architecture · Computer Science 2024-09-11 Dongjae Lee , Bongjoon Hyun , Taehun Kim , Minsoo Rhu

Recent research demonstrated the promise of using resistive random access memory (ReRAM) as an emerging technology to perform inherently parallel analog domain in-situ matrix-vector multiplication -- the intensive and key computation in…

Processing in memory (PiM) represents a promising computing paradigm to enhance performance of numerous data-intensive applications. Variants performing computing directly in emerging nonvolatile memories can deliver very high energy…

Memory and logic integration on the same chip is becoming increasingly cost effective, creating the opportunity to offload data-intensive functionality to processing units placed inside memory chips. The introduction of memory-side…

Hardware Architecture · Computer Science 2017-08-23 Javier Picorel , Djordje Jevdjic , Babak Falsafi

The memory controller is in charge of managing DRAM maintenance operations (e.g., refresh, RowHammer protection, memory scrubbing) to reliably operate modern DRAM chips. Implementing new maintenance operations often necessitates…

Hardware Architecture · Computer Science 2025-08-07 Hasan Hassan , Ataberk Olgun , A. Giray Yaglikci , Haocong Luo , Onur Mutlu

Existing memory management techniques severely hinder efficient Large Language Model serving on accelerators constrained by poor random-access bandwidth.While static pre-allocation preserves memory contiguity,it incurs significant overhead…

Hardware Architecture · Computer Science 2026-04-22 Guoqiang Zou , Wanyu Wang , Hao Zheng , Longxiang Yin , Yinhe Han

Heterogeneous Memory Architecture (HMA) aims to optimize memory usage by leveraging a combination of memory types, such as high-bandwidth memory (HBM), commodity DRAM, and non-volatile memory (NVM), when utilized as main memory. To achieve…

Hardware Architecture · Computer Science 2026-04-23 Upasna , Venkata Kalyan Tavva