English
Related papers

Related papers: Reliable Generation of High-Performance Matrix Alg…

200 papers

Large language models (LLMs) have demonstrated significant potential in code generation tasks. However, there remains a performance gap between open-source and closed-source models. To address this gap, existing approaches typically…

Computation and Language · Computer Science 2025-04-18 Weijie Lv , Xuan Xia , Sheng-Jun Huang

High-level synthesis (HLS) allows hardware designers to create hardware designs with high-level programming languages like C/C++/OpenCL, which greatly improves hardware design productivity. However, existing HLS flows require programmers'…

Hardware Architecture · Computer Science 2024-10-11 Haocheng Xu , Haotian Hu , Sitao Huang

Despite significant investment in software infrastructure, machine learning systems, runtimes and compilers do not compose properly. We propose a new design aiming at providing unprecedented degrees of modularity, composability and…

BLASFEO is a dense linear algebra library providing high-performance implementations of BLAS- and LAPACK-like routines for use in embedded optimization and other applications targeting relatively small matrices. BLASFEO defines an API which…

Mathematical Software · Computer Science 2020-06-09 Gianluca Frison , Tommaso Sartor , Andrea Zanelli , Moritz Diehl

Tensor algebra is a crucial component for data-intensive workloads such as machine learning and scientific computing. As the complexity of data grows, scientists often encounter a dilemma between the highly specialized dense tensor algebra…

Programming Languages · Computer Science 2024-07-19 Mahdi Ghorbani , Emilien Bauer , Tobias Grosser , Amir Shaikhha

High-Level Synthesis (HLS) tools are widely adopted in FPGA-based domain-specific accelerator design. However, existing tools rely on fixed optimization strategies inherited from software compilations, limiting their effectiveness.…

Achieving high-performance GPU kernels requires optimizing algorithm implementations to the targeted GPU architecture. It is of utmost importance to fully use the compute and memory hierarchy, as well as available specialised hardware.…

Programming Languages · Computer Science 2020-03-16 Bastian Hagedorn , Archibald Samuel Elliott , Henrik Barthels , Rastislav Bodik , Vinod Grover

Fault tolerance is a major concern in distributed computational settings. In the classic master-worker setting, a server (the master) needs to perform some heavy computation which it may distribute to $m$ other machines (workers) in order…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-30 Keren Censor-Hillel , Yuka Machino , Pedro Soto

GPUs are dedicated processors used for complex calculations and simulations and they can be effectively used for tropical algebra computations. Tropical algebra is based on max-plus algebra and min-plus algebra. In this paper we proposed…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-03-22 Ahsan Humayun , Dr. Muhammad Asif , Dr. Muhammmad Kashif Hanif

A tight lower bound for required I/O when computing an ordinary matrix-matrix multiplication on a processor with two layers of memory is established. Prior work obtained weaker lower bounds by reasoning about the number of segments needed…

Computational Complexity · Computer Science 2019-02-07 Tyler Michael Smith , Bradley Lowery , Julien Langou , Robert A. van de Geijn

We factor Beamer's push-pull, also known as direction-optimized breadth-first-search (DOBFS) into 3 separable optimizations, and analyze them for generalizability, asymptotic speedup, and contribution to overall speedup. We demonstrate that…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-06-21 Carl Yang , Aydin Buluc , John D. Owens

Sparse linear algebra is central to many scientific programs, yet compilers fail to optimize it well. High-performance libraries are available, but adoption costs are significant. Moreover, libraries tie programs into vendor-specific…

Performance · Computer Science 2020-01-29 Philip Ginsbach , Bruce Collie , Michael F. P. O'Boyle

As multicore systems continue to gain ground in the High Performance Computing world, linear algebra algorithms have to be reformulated or new algorithms have to be developed in order to take advantage of the architectural features on these…

Mathematical Software · Computer Science 2008-06-12 Alfredo Buttari , Julien Langou , Jakub Kurzak , Jack Dongarra

Tensor algebra finds applications in various domains, and these applications, especially when accelerated on spatial hardware accelerators, can deliver high performance and low power. Spatial hardware accelerator exhibits complex design…

Hardware Architecture · Computer Science 2021-04-27 Liancheng Jia , Zizhang Luo , Liqiang Lu , Yun Liang

There is a trend towards increased specialization of data management software for performance reasons. In this paper, we study the automatic specialization and optimization of database application programs -- sequences of queries and…

We present a new approach to fault tolerance for High Performance Computing system. Our approach is based on a careful adaptation of the Algorithmic Based Fault Tolerance technique (Huang and Abraham, 1984) to the need of parallel…

Distributed, Parallel, and Cluster Computing · Computer Science 2008-06-20 George Bosilca , Remi Delmas , Jack Dongarra , Julien Langou

Sparse compiler is a promising solution for sparse tensor algebra optimization. In compiler implementation, reduction in sparse-dense hybrid algebra plays a key role in performance. Though GPU provides various reduction semantics that can…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-01-10 Genghan Zhang , Yuetong Zhao , Yanting Tao , Zhongming Yu , Guohao Dai , Sitao Huang , Yuan Wen , Pavlos Petoumenos , Yu Wang

Across a wide range of hardware scenarios, the computational efficiency and physical size of the arithmetic units significantly influence the speed and footprint of the overall hardware system. Nevertheless, the effectiveness of prior…

Machine Learning · Computer Science 2024-05-14 Yao Lai , Jinxin Liu , David Z. Pan , Ping Luo

Widely used compilers like GCC and LLVM usually have hundreds of optimizations controlled by optimization flags, which are enabled or disabled during compilation to improve runtime performance (e.g., small execution time) of the compiler…

Programming Languages · Computer Science 2023-05-01 Mingxuan Zhu , Dan Hao , Junjie Chen

Bayesian optimization (BO) provides a powerful framework for optimizing black-box, expensive-to-evaluate functions. It is therefore an attractive tool for engineering design problems, typically involving multiple objectives. Thanks to the…

Machine Learning · Computer Science 2024-09-06 Navid Ansari , Alireza Javanmardi , Eyke Hüllermeier , Hans-Peter Seidel , Vahid Babaei
‹ Prev 1 4 5 6 7 8 10 Next ›