42 citations · 59 across the 10 of their papers we have counts for
12 papers
REPORT-OPS: Hybrid Evidence-Guided Reporting with Human-Supervised Refinement for HPC
Mah Kadidia Konate, Mayur Akewar, Janki Bhimani +1
Operational reporting for high-performance computing (HPC) facilities requires combining information from monitoring services, schedulers, incident and maintenance records, storage…
Do Time-Series QA Systems Read the Time Series? Evidence Use and Reasoning Reliability
Zhuomin Chen, Jingchao Ni, Xu Zheng +4
In recent years, time-series question answering (QA) systems have made significant progress. However, generating a correct answer does not show whether retaining the supplied numer…
Towards A Unified Information Bottleneck Framework for Time Series Explanations
Xu Zheng, Zichuan Liu, Zhuomin Chen +7
Explaining deep learning models operating on time series data is crucial in various applications that require transparent and interpretable insights into model behavior. {Existing…
Idiosyncrasies of Programmable Caching Engines
José Peixoto, Alexis Gonzalez, Janki Bhimani +4
Programmable caching engines like CacheLib are widely used in production systems to support diverse workloads in multi-tenant environments. CacheLib's design focuses on performance…
Aurora: Neuro-Symbolic AI Driven Advising Agent
Lorena Amanda Quincoso Lugones, Christopher Kverne, Nityam Sharadkumar Bhimani +4
Academic advising in higher education is under severe strain, with advisor-to-student ratios commonly exceeding 300:1. These structural bottlenecks limit timely access to guidance,…
WSBD: Freezing-Based Optimizer for Quantum Neural Networks
Christopher Kverne, Mayur Akewar, Yuqian Huo +2
The training of Quantum Neural Networks (QNNs) is hindered by the high computational cost of gradient estimation and the barren plateau problem, where optimization landscapes becom…
KORAL: Knowledge Graph Guided LLM Reasoning for SSD Operational Analysis
Mayur Akewar, Sandeep Madireddy, Dongsheng Luo +1
Solid State Drives (SSDs) are critical to datacenters, consumer platforms, and mission-critical systems. Yet diagnosing their performance and reliability is difficult because data…
Preparation Meets Opportunity: Enhancing Data Preprocessing for ML Training With Seneca
Omkar Desai, Ziyang Jiao, Shuyi Pei +2
Input data preprocessing is a common bottleneck when concurrently training multimedia machine learning (ML) models in modern systems. To alleviate these bottlenecks and reduce the…
Revisiting Noise-adaptive Transpilation in Quantum Computing: How Much Impact Does it Have?
Yuqian Huo, Jinbiao Wei, Christopher Kverne +3
Transpilation, particularly noise-aware optimization, is widely regarded as essential for maximizing the performance of quantum circuits on superconducting quantum computers. The c…
I/O Workload Management for All-Flash Datacenter Storage Systems Based on Total Cost of Ownership
Zhengyu Yang, Manu Awasthi, Mrinmoy Ghosh +2
Recently, the capital expenditure of flash-based Solid State Driver (SSDs) keeps declining and the storage capacity of SSDs keeps increasing. As a result, all-flash storage systems…
AutoTiering: Automatic Data Placement Manager in Multi-Tier All-Flash Datacenter
Zhengyu Yang, Morteza Hoseinzadeh, Allen Andrews +6
In the year of 2017, the capital expenditure of Flash-based Solid State Drivers (SSDs) keeps declining and the storage capacity of SSDs keeps increasing. As a result, the "selling…
Pelletization Characteristics of the Hydrothermal Pretreated Rice Straw with Added Binders
Xianfei Xia, Hongru Xiao, Zhengyu Yang +2
Pelletization of the loose rice straw is an attractive option to produce renewable fuels. In this paper, we focus on the problem of how to improve this pelletization process, espec…