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To achieve peak performance on modern GPUs, one must balance two frames of mind: issuing instructions to individual threads to control their behavior, while simultaneously tracking the convergence of many threads acting in concert to…

Programming Languages · Computer Science 2025-11-18 Manya Bansal , Daniel Sainati , Joseph W. Cutler , Saman Amarasinghe , Jonathan Ragan-Kelley

Programming by Example (PBE) is the task of inducing computer programs from input-output examples. It can be seen as a type of machine learning where the hypothesis space is the set of legal programs in some programming language. Recent…

Programming Languages · Computer Science 2017-03-03 John K. Feser , Marc Brockschmidt , Alexander L. Gaunt , Daniel Tarlow

We introduce process-oriented programming as a natural extension of object-oriented programming for parallel computing. It is based on the observation that every class of an object-oriented language can be instantiated as a process,…

Programming Languages · Computer Science 2014-07-22 Edward Givelberg

Parallel parameterized complexity theory studies how fixed-parameter tractable (fpt) problems can be solved in parallel. Previous theoretical work focused on parallel algorithms that are very fast in principle, but did not take into account…

Data Structures and Algorithms · Computer Science 2019-02-21 Max Bannach , Malte Skambath , Till Tantau

Partitioned Global Address Space (PGAS) integrates the concepts of shared memory programming and the control of data distribution and locality provided by message passing into a single parallel programming model. The purpose of allying…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-15 Kamran Idrees , Christoph Niethammer , Aniello Esposito , Colin W. Glass

A Partitioned Global Address Space (PGAS) approach treats a distributed system as if the memory were shared on a global level. Given such a global view on memory, the user may program applications very much like shared memory systems. This…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-07-08 Huan Zhou , Yousri Mhedheb , Kamran Idrees , Colin W. Glass , José Gracia , Karl Fürlinger , Jie Tao

In large language model (LLM) training, several parallelization strategies, including Tensor Parallelism (TP), Pipeline Parallelism (PP), Data Parallelism (DP), as well as Sequence Parallelism (SP) and Context Parallelism (CP), are employed…

Machine Learning · Computer Science 2024-11-12 Kazuki Fujii , Kohei Watanabe , Rio Yokota

Embedded system performances are bounded by power consumption. The trend is to offload greedy computations on hardware accelerators as GPU, Xeon Phi or FPGA. FPGA chips combine both flexibility of programmable chips and energy-efficiency of…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-01-16 Christophe Alias

This paper presents language techniques for applying memoization selectively. The techniques provide programmer control over equality, space usage, and identification of precise dependences so that memoization can be applied according to…

Programming Languages · Computer Science 2011-06-03 Umut A. Acar , Guy E. Blelloch , Robert Harper

Space is a circuit oriented, spatial programming language designed to exploit the massive parallelism available in a novel formal model of computation called the Synchronic A-Ram, and physically related FPGA and reconfigurable…

Computation and Language · Computer Science 2010-08-31 Alex V Berka

Parameter-Efficient Fine-tuning (PEFT) facilitates the fine-tuning of Large Language Models (LLMs) under limited resources. However, the fine-tuning performance with PEFT on complex, knowledge-intensive tasks is limited due to the…

Computation and Language · Computer Science 2024-06-10 Jitai Hao , WeiWei Sun , Xin Xin , Qi Meng , Zhumin Chen , Pengjie Ren , Zhaochun Ren

The persistent programming systems of the 1980s offered a programming model that integrated computation and long-term storage. In these systems, reliable applications could be engineered without requiring the programmer to write translation…

Distributed, Parallel, and Cluster Computing · Computer Science 2010-06-21 Alan Dearle , Graham Kirby , Stuart Norcross , Andrew McCarthy

Parallel programs are frequently modeled as dependency or cost graphs, which can be used to detect various bugs, or simply to visualize the parallel structure of the code. However, such graphs reflect just one particular execution and are…

Programming Languages · Computer Science 2023-11-14 Francis Rinaldi , june wunder , Arthur Aevedo De Amorim , Stefan K. Muller

Irregular memory access patterns pose performance and user productivity challenges on distributed-memory systems. They can lead to fine-grained remote communication and the data access patterns are often not known until runtime. The…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-03-27 Thomas B. Rolinger , Christopher D. Krieger , Alan Sussman

We present DASH, a C++ template library that offers distributed data structures and parallel algorithms and implements a compiler-free PGAS (partitioned global address space) approach. DASH offers many productivity and performance features…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-10-06 Karl Fürlinger , Tobias Fuchs , Roger Kowalewski

Modern architectures require applications to make effective use of caches to achieve high performance and hide memory latency. This in turn requires careful consideration of placement of data in memory to exploit spatial locality, leverage…

Programming Languages · Computer Science 2019-01-24 Juliana Franco , Alexandros Tasos , Sophia Drossopoulou , Tobias Wrigstad , Susan Eisenbach

Functional programming languages are particularly well-suited for building automated reasoning systems, since (among other reasons) a logical term is well modeled by an inductive type, traversing a term can be implemented generically as a…

Programming Languages · Computer Science 2020-06-02 Daniel Selsam , Simon Hudon , Leonardo de Moura

FFT (fast Fourier transform) plays a very important role in many fields, such as digital signal processing, digital image processing and so on. However, in application, FFT becomes a factor of affecting the processing efficiency, especially…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-07-25 Fan Zhang , Chen Hu , Qiang Yin , Wei Hu

The $hp$-adaptive finite element method (FEM) - where one independently chooses the mesh size ($h$) and polynomial degree ($p$) to be used on each cell - has long been known to have better theoretical convergence properties than either $h$-…

Numerical Analysis · Mathematics 2023-09-14 Marc Fehling , Wolfgang Bangerth

Task based parallel programming has shown competitive outcomes in many aspects of parallel programming such as efficiency, performance, productivity and scalability. Different approaches are used by different software development frameworks…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-05-09 Afshin Zafari