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20212026
most citedSizey: Memory-Efficient Execution of Scientific Workflow Tasks

9 citations · 25 across the 14 of their papers we have counts for

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Showing 2026Show all

7 papers · 1 filter

cs.LG2026

E8 Lattice Key Quantization for Low-Bit KV-Cache Compression

Sasho Nedelkoski, Alexander Acker, Soeren Becker +2

Compressing the key-value (KV) cache is essential for serving long-context large language models (LLMs) under memory constraints. While current scalar quantization methods achieve…

cs.DC2026

Reconciling Bottom-Up Metrics with Top-Down Reporting for Cloud Carbon Accounting

Philipp Wiesner, Loïc Lannelongue, Alexander Acker +1

Organizations seeking to reduce the carbon footprint of their cloud applications must rely on two largely disconnected ways of measuring it, each with important limitations. Bottom…

cs.LG2026

Collaborative Reasoning Distillation via Cross-Feedback and Coherent Curation

Taehoon Kim, Seunggeun Cho, Dongsu Han

Reasoning capabilities are critical for advancing Large Language Models, yet current approaches either require massive computational budgets or struggle to effectively distill reas…

cs.DC2026

About the Influence of Workflow Topology on Task Intensity Prediction through Graph Learning

Max Otto, Haci Ismail Aslan, Joel Witzke +2

Efficient resource provisioning for large-scale workflows on cloud infrastructures is a critical performance engineering challenge. These workflows are often structured as directed…

cs.AI2026★ 3 cited

Scalable and Data-Driven Decision Support in the Maintenance, Repair, and Overhaul Process

Houkun Zhu, Helena Ebel, Dominik Scheinert +3

Several businesses apply maintenance, repair, and overhaul (MRO) principles to the life-cycle of their existing products. In cases like casted gas turbine component Product Lifecyc…

cs.DC2026★ 1 cited

Optimizing Memory Allocation in Distributed Clusters with Predictive Modeling

Jonathan Bader, Edgar Blumenthal, Marten Eckardt +5

In modern distributed systems, efficient resource allocation is a vital aspect to maintain scalability, reduce operational costs, and ensure fast execution even across heterogeneou…

cs.DC2026

Beyond Microservices: Testing Web-Scale RCA Methods on GPU-Driven LLM Workloads

Dominik Scheinert, Alexander Acker, Thorsten Wittkopp +6

Large language model (LLM) services have become an integral part of search, assistance, and decision-making applications. However, unlike traditional web or microservices, the hard…