English
Related papers

Related papers: Bespoke OLAP: Synthesizing Workload-Specific One-s…

200 papers

The overwhelmingly increasing amount of stored data has spurred researchers seeking different methods in order to optimally take advantage of it which mostly have faced a response time problem as a result of this enormous size of data. Most…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-02-18 H I Alzeini , Sh A Hameed , M H Habaebi

We describe a system called Overton, whose main design goal is to support engineers in building, monitoring, and improving production machine learning systems. Key challenges engineers face are monitoring fine-grained quality, diagnosing…

Machine Learning · Computer Science 2019-09-13 Christopher Ré , Feng Niu , Pallavi Gudipati , Charles Srisuwananukorn

Datalog-based languages are regaining popularity as a powerful abstraction for expressing recursive computations in domains such as program analysis and graph processing. However, existing systems often face a trade-off between efficiency…

Databases · Computer Science 2025-11-18 Hangdong Zhao , Zhenghong Yu , Srinag Rao , Simon Frisk , Zhiwei Fan , Paraschos Koutris

Despite the rapid development of large language models (LLMs), a fundamental challenge persists: the lack of high-quality optimization modeling datasets hampers LLMs' robust modeling of practical optimization problems from natural language…

Artificial Intelligence · Computer Science 2025-02-24 Hongliang Lu , Zhonglin Xie , Yaoyu Wu , Can Ren , Yuxuan Chen , Zaiwen Wen

Pipelining between data loading and computation is a critical tensor program optimization for GPUs. In order to unleash the high performance of latest GPUs, we must perform a synergetic optimization of multi-stage pipelining across the…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-05-09 Guyue Huang , Yang Bai , Liu Liu , Yuke Wang , Bei Yu , Yufei Ding , Yuan Xie

Existing research on single-machine scheduling is largely focused on exact algorithms, which perform well on typical instances but can significantly deteriorate on certain regions of the problem space. In contrast, data-driven approaches…

Machine Learning · Computer Science 2025-10-08 Nikolai Antonov , Prěmysl Šůcha , Mikoláš Janota , Jan Hůla

Large-scale optimization is a key backbone of modern business decision-making. However, building these models is often labor-intensive and time-consuming. We address this by proposing LEAN-LLM-OPT, a LightwEight AgeNtic workflow…

Artificial Intelligence · Computer Science 2026-02-03 Kuo Liang , Yuhang Lu , Jianming Mao , Shuyi Sun , Chunwei Yang , Congcong Zeng , Xiao Jin , Hanzhang Qin , Ruihao Zhu , Chung-Piaw Teo

Large language models (LLMs) are increasingly explored for their reasoning capabilities, yet their ability to perform structured, constraint-based optimization from natural language remains insufficiently understood. This study evaluates…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-18 Aasish Kumar Sharma , Julian Kunkel

Large language models (LLMs) are increasingly expected to go beyond simple factual queries toward Deep Research-tasks that require decomposing questions into sub-problems, coordinating multi-step reasoning, and synthesizing evidence from…

Computation and Language · Computer Science 2025-09-03 Ziyi Xia , Kun Luo , Hongjin Qian , Zheng Liu

Modern enterprise platforms increasingly depend on distributed microservices, analytical data platforms, and external APIs to construct composite responses for applications. Orchestrating data retrieval across these heterogeneous systems is…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-03-11 Abhiram Kandiraju

Real-world enterprise data intelligence workflows encompass data engineering that turns raw sources into analytical-ready tables and data analysis that convert those tables into decision-oriented insights. We introduce DAComp, a benchmark…

Computation and Language · Computer Science 2025-12-05 Fangyu Lei , Jinxiang Meng , Yiming Huang , Junjie Zhao , Yitong Zhang , Jianwen Luo , Xin Zou , Ruiyi Yang , Wenbo Shi , Yan Gao , Shizhu He , Zuo Wang , Qian Liu , Yang Wang , Ke Wang , Jun Zhao , Kang Liu

With the rapid advancement of large language models (LLMs), efficiently serving LLM inference under limited GPU resources has become a critical challenge. Recently, an increasing number of studies have explored applying serverless computing…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-02-19 Zijie Su , Muhammed Tawfiqul Islam , Mohammad Goudarzi , Adel N. Toosi

Synthetic data has emerged as a crucial solution to the data scarcity bottleneck in large language models (LLMs), particularly for specialized domains and low-resource languages. However, the broader adoption of existing synthetic data…

Machine Learning · Computer Science 2026-05-12 Zhichao Shi , Cehao Yang , Hao Zhou , Xiaojun Wu , Huajie Li , Xuhui Jiang , Chengjin Xu , Yuanzhuo Wang , Jian Guo

Large language models (LLMs) have emerged as powerful tools for automatic algorithm design (AAD). However, existing pipelines remain inefficient. They operate at the granularity of full algorithms, redundantly rewriting recurring…

Artificial Intelligence · Computer Science 2026-05-12 Maxime Bouscary , Manxi Wu , Saurabh Amin

Optimizing data movements is becoming one of the biggest challenges in heterogeneous computing to cope with data deluge and, consequently, big data applications. When creating specialized accelerators, modern high-level synthesis (HLS)…

Hardware Architecture · Computer Science 2022-11-09 Stephanie Soldavini , Donatella Sciuto , Christian Pilato

Customers' load profiles are critical resources to support data analytics applications in modern power systems. However, there are usually insufficient historical load profiles for data analysis, due to the collection cost and data privacy…

Machine Learning · Computer Science 2024-02-14 Zhenyi Wang , Hongcai Zhang

Large Language Models (LLMs) have shown remarkable proficiency in natural language understanding (NLU), opening doors for innovative applications. We introduce StreamLink - an LLM-driven distributed data system designed to improve the…

Databases · Computer Science 2025-05-29 Dawei Feng , Di Mei , Huiri Tan , Lei Ren , Xianying Lou , Zhangxi Tan

Machine learning (ML) has become a vital part in many aspects of our daily life. However, building well performing machine learning applications requires highly specialized data scientists and domain experts. Automated machine learning…

Machine Learning · Computer Science 2021-01-27 Marc-André Zöller , Marco F. Huber

Automated machine learning (AutoML) frameworks have become important tools in the data scientists' arsenal, as they dramatically reduce the manual work devoted to the construction of ML pipelines. Such frameworks intelligently search among…

Machine Learning · Computer Science 2024-12-31 Teddy Lazebnik , Amit Somech , Abraham Itzhak Weinberg

Evaluating Text-to-SQL agents in private business intelligence (BI) settings is challenging due to the scarcity of realistic, domain-specific data. While synthetic evaluation data offers a scalable solution, existing generation methods fail…

Computation and Language · Computer Science 2026-01-22 Jinhui Liu , Ximeng Zhang , Yanbo Ai , Zhou Yu