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Related papers: Chiplets and the Codelet Model

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Experience shows that on today's high performance systems the utilization of different acceleration cards in conjunction with a high utilization of all other parts of the system is difficult. Future architectures, like exascale clusters,…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-03-07 Patrick Diehl , Madhavan Seshadri , Thomas Heller , Hartmut Kaiser

Processing data received as a stream is a task commonly performed by modern embedded devices, in a wide range of applications such as multimedia (encoding/decoding/ playing media), networking (switching and routing), digital security,…

Hardware Architecture · Computer Science 2014-03-31 I. B. Nawinne , M. S. Wickramasinghe , R. G. Ragel , S. Radhakrishnan

The \emph{Partial Cache-Coherence (PCC)} model maintains hardware cache coherence only within subsets of cores, enabling large-scale memory sharing with emerging memory interconnect technologies like Compute Express Link (CXL). However,…

Operating Systems · Computer Science 2025-11-11 Fangnuo Wu , Mingkai Dong , Wenjun Cai , Jingsheng Yan , Haibo Chen

The growing demand for compute-intensive applications has made multi-chiplet architectures a promising alternative to monolithic designs, offering improved scalability and manufacturing flexibility. However, effectively managing the…

Hardware Architecture · Computer Science 2026-01-27 Zizhen Liu , Fangzhiyi Wang , Mengdi Wang , Jing Ye , Hayden Kwok-Hay So , Cheng Liu , Huawei Li

Frontier models increasingly adopt Mixture-of-Experts (MoE) architectures to achieve large-model performance at reduced cost. However, training MoE models on HPC platforms is hindered by large memory footprints, frequent large-scale…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-07 Sajal Dash , Feiyi Wang

The rapid advancement of embedded multicore and many-core systems has revolutionized computing, enabling the development of high-performance, energy-efficient solutions for a wide range of applications. As models scale up in size, data…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-15 Ruhai Lin , Rui-Jie Zhu , Jason K. Eshraghian

Many modern and emerging applications must process increasingly large volumes of data. Unfortunately, prevalent computing paradigms are not designed to efficiently handle such large-scale data: the energy and performance costs to move this…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-07-31 Saugata Ghose , Amirali Boroumand , Jeremie S. Kim , Juan Gómez-Luna , Onur Mutlu

Advanced packaging and chiplet-based integration are increasingly adopted to build complex heterogeneous systems beyond the limits of monolithic scaling. While these architectures offer major benefits in terms of modularity, yield, and…

Cryptography and Security · Computer Science 2026-05-11 Giorgio Di Natale , Christelle Rabache , Pierre-Louis Hellier , Florence Podevin , Sylvain Bourdel , Romain Siragusa , Paolo Maistri

Motivation: With the development of droplet based systems, massive single cell transcriptome data has become available, which enables analysis of cellular and molecular processes at single cell resolution and is instrumental to…

Machine Learning · Computer Science 2018-12-27 Tiehang Duan , José P. Pinto , Xiaohui Xie

In-memory computing (IMC) on a monolithic chip for deep learning faces dramatic challenges on area, yield, and on-chip interconnection cost due to the ever-increasing model sizes. 2.5D integration or chiplet-based architectures interconnect…

Machine Learning · Computer Science 2021-08-23 Gokul Krishnan , Sumit K. Mandal , Manvitha Pannala , Chaitali Chakrabarti , Jae-sun Seo , Umit Y. Ogras , Yu Cao

Heterogeneity is omnipresent in today's commodity computational systems, which comprise at least one multi-core Central Processing Unit (CPU) and one Graphics Processing Unit (GPU). Nonetheless, all this computing power is not being…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-02-18 Hervé Paulino , Eduardo Marques

The advent of high performance computing (HPC) and graphics processing units (GPU), present an enormous computation resource for Large data transactions (big data) that require parallel processing for robust and prompt data analysis. While…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-10-17 Kato Mivule , Benjamin Harvey , Crystal Cobb , Hoda El Sayed

This paper introduces a versatile, multi-layered technology to help support teaching and learning core computer architecture concepts. This technology, called CodeAPeel is already implemented in one particular form to describe instruction…

Hardware Architecture · Computer Science 2021-11-30 A. Yavuz Oruc , A. Atmaca , Y. Nevzat Sengun , A. Semi Yenimol

A common paradigm for scientific computing is distributed message-passing systems, and a common approach to these systems is to implement them across clusters of high-performance workstations. As multi-core architectures become increasingly…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-05-01 Christine Task , Arun Chauhan

Deploying large language models (LLMs) for online inference is often constrained by limited GPU memory, particularly due to the growing KV cache during auto-regressive decoding. Hybrid GPU-CPU execution has emerged as a promising solution…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-01-16 Jiakun Fan , Yanglin Zhang , Xiangchen Li , Dimitrios S. Nikolopoulos

Compute Express Link (CXL) is a rapidly emerging coherent interconnect standard that provides opportunities for memory pooling and sharing. Memory sharing is a well-established software feature that improves memory utilization by avoiding…

Emerging Technologies · Computer Science 2024-04-05 Sunita Jain , Nagaradhesh Yeleswarapu , Hasan Al Maruf , Rita Gupta

The electrical and electronic engineering has used parallel programming to solve its large scale complex problems for performance reasons. However, as parallel programming requires a non-trivial distribution of tasks and data, developers…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-07-05 Antonio Wendell De Oliveira Rodrigues , Frédéric Guyomarc'H , Jean-Luc Dekeyser , Yvonnick Le Menach

MPSoCs are gaining popularity because of its potential to solve computationally expensive applications. A multi-core processor combines two or more independent cores (normally a CPU) into a single package composed of a single integrated…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-04-14 Bilal Habib , Ahmed Anber , Sultan Daud Khan

Large Language Models (LLMs) with the Mixture-of-Experts (MoE) architectures have shown promising performance on various tasks. However, due to the huge model sizes, running them in resource-constrained environments where the GPU memory is…

Machine Learning · Computer Science 2025-05-02 Keisuke Kamahori , Tian Tang , Yile Gu , Kan Zhu , Baris Kasikci

Currently engineering efficient and successful event-driven applications based on the emerging Complex Event Processing (CEP) technology, is a laborious trial and error process. The proposed CEP design pattern approach should support CEP…

Software Engineering · Computer Science 2008-06-09 Adrian Paschke