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Efficiently serving Large Language Models (LLMs) requires selecting an optimal parallel execution plan, balancing computation, memory, and communication overhead. However, determining the best strategy is challenging due to varying…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-01 Yi-Chien Lin , Woosuk Kwon , Ronald Pineda , Fanny Nina Paravecino

Writing efficient hybrid parallel code is tedious, error-prone, and requires good knowledge of both parallel programming and multithreading such as MPI and OpenMP, resp. Therefore, we present a framework which is based on a job model that…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-07-03 Ralf-Peter Mundani , Marko Ljucović , Ernst Rank

This paper proposes a general formulation for temporal parallelisation of dynamic programming for optimal control problems. We derive the elements and associative operators to be able to use parallel scans to solve these problems with…

Optimization and Control · Mathematics 2022-01-25 Simo Särkkä , Ángel F. García-Fernández

In this paper, we introduce a software-defined framework that enables the parallel utilization of all the programmable processing resources available in heterogeneous system-on-chip (SoC) including FPGA-based hardware accelerators and…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-02-12 Jose Nunez-Yanez , Mohammad Hosseinabady , Moslem Amiri , Andrés Rodríguez , Rafael Asenjo , Angeles Navarro , Rubén Gran-Tejero , Darío Suárez-Gracia

State-of-the-art approaches to design, develop and optimize software packet-processing programs are based on static compilation: the compiler's input is a description of the forwarding plane semantics and the output is a binary that can…

Networking and Internet Architecture · Computer Science 2021-06-17 Sebastiano Miano , Alireza Sanaee , Fulvio Risso , Gábor Rétvári , Gianni Antichi

GCC has a new infrastructure to support a link time optimization (LTO). The infrastructure is designed to allow linking of large applications using a special mode (WHOPR) which support parallelization of the compilation process. In this…

Programming Languages · Computer Science 2010-11-05 T. Glek , J. Hubicka

As software becomes larger, programming languages become higher-level, and processors continue to fail to be clocked faster, we'll increasingly require compilers to reduce code bloat, eliminate abstraction penalties, and exploit interesting…

Programming Languages · Computer Science 2018-09-10 Nuno P. Lopes , John Regehr

Sequential algorithms for the Stable Matching Problem are often too slow in the context of some large scale applications like switch scheduling. Parallel architectures can offer a notable decrease in runtime complexity. We propose a stable…

Data Structures and Algorithms · Computer Science 2024-08-27 Scott Wynn , Alec Kyritsis , Stephora Alberi , Enyue Lu

Real-time and cyber-physical systems need to interact with and respond to their physical environment in a predictable time. While multicore platforms provide incredible computational power and throughput, they also introduce new sources of…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-06-29 Ayoosh Bansal , Jayati Singh , Yifan Hao , Jen-Yang Wen , Renato Mancuso , Marco Caccamo

A method is presented for parallelizing the computation of solutions to discrete-time, linear-quadratic, finite-horizon optimal control problems, which we will refer to as LQR problems. This class of problem arises frequently in robotic…

Optimization and Control · Mathematics 2018-09-18 Forrest Laine , Claire Tomlin

Power consumption is a critical consideration in high performance computing systems and it is becoming the limiting factor to build and operate Petascale and Exascale systems. When studying the power consumption of existing systems running…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-01-27 Radim Vavřík , Antoni Portero , Štěpán Kuchař , Martin Golasowski , Simone Libutti , Giuseppe Massari , William Fornaciari , Vít Vondrák

Traditional heterogeneous parallel algorithms, designed for heterogeneous clusters of workstations, are based on the assumption that the absolute speed of the processors does not depend on the size of the computational task. This assumption…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-09-15 Alexey Lastovetsky , Ravi Reddy , Vladimir Rychkov , David Clarke

Structured LLM workflows, where specialized LLM sub-agents execute according to a predefined graph, have become a powerful abstraction for solving complex tasks. Optimizing such workflows, i.e., selecting configurations for each sub-agent…

Computation and Language · Computer Science 2026-05-14 Junyan Li , Zhang-Wei Hong , Maohao Shen , Yang Zhang , Chuang Gan

The multi-level hp-refinement scheme is a powerful extension of the finite element method that allows local mesh adaptation without the trouble of constraining hanging nodes. This is achieved through hierarchical high-order overlay meshes,…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-12-05 John N. Jomo , Nils Zander , Mohamed Elhaddad , Ali Özcan , Stefan Kollmannsberger , Ralf-Peter Mundani , Ernst Rank

Lossy compression is one of the most efficient solutions to reduce storage overhead and improve I/O performance for HPC applications. However, existing parallel I/O libraries cannot fully utilize lossy compression to accelerate parallel…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-30 Sian Jin , Dingwen Tao , Houjun Tang , Sheng Di , Suren Byna , Zarija Lukic , Franck Cappello

Load balancing, operator instance collocations and horizontal scaling are critical issues in Parallel Stream Processing Engines to achieve low data processing latency, optimized cluster utilization and minimized communication cost…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-02-12 Kasper Grud Skat Madsen , Yongluan Zhou , Jianneng Cao

Applications in science and engineering often require huge computational resources for solving problems within a reasonable time frame. Parallel supercomputers provide the computational infrastructure for solving such problems. A…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Rajesh Sudarsan , Calvin J. Ribbens

Heterogeneous multi-core architectures combine on a single chip a few large, general-purpose host cores, optimized for single-thread performance, with (many) clusters of small, specialized, energy-efficient accelerator cores for…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-12 Luca Colagrande , Luca Benini

Efficient matching of incoming events of data streams to persistent queries is fundamental to event stream processing systems. These applications require dealing with high volume and continuous data streams with fast processing time on…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-06-05 Fuyuan Xiao , Masayoshi Aritsugi

Hardware accelerators, such as those based on GPUs and FPGAs, offer an excellent opportunity to efficiently parallelize functionalities. Recently, modern embedded platforms started being equipped with such accelerators, resulting in a…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-05-16 Daniel Casini , Paolo Pazzaglia , Alessandro Biondi , Marco Di Natale
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