Distributed Systems • Cloud Native • Research

Tracking the systems behind modern compute.

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arXiv Distributed Computing

Asynchronous Parallel Search for Exact Multi-Objective Shortest Paths with Versioned Frontier Snapshots and Indexed Dominance Pruning

arXiv:2609.11944v1 Announce Type: new Abstract: Exact multi-objective shortest-path (MOSP) search computes the complete Pareto set between specified start and goal vertices, and its computational cost can grow rapidly with expanding nondominated label sets and frequent dominance tests over per-vertex Pareto frontiers…

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arXiv Distributed Computing

Hyperion: An AI-powered HPC cluster for sciences and humanities research that utilizes ML for predicting job turnaround time

arXiv:2609.11946v1 Announce Type: new Abstract: Hyperion is an innovative high-performance computing (HPC) cluster developed for researchers in both science and humanities disciplines at the University of South Carolina (USC). Our approach involved constructing a HPC cluster designed to meet the current research needs…

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arXiv Distributed Computing

Specifying Paxos for System Builders: Pseudocode Made Executable

arXiv:2609.12239v1 Announce Type: new Abstract: This paper presents a precise executable specification---as a faithful mapping from the pseudocode---of Paxos for System Builders, a practical protocol for replication and consensus in distributed systems. Paxos for System Builders has both a robust implementation in C a…

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arXiv Distributed Computing

HeatCache: Thermal-aware Energy-efficient LLM Inference Scheduling for Chassis-level Liquid Cooling in Sustainable Edge Server Rooms

arXiv:2609.12449v1 Announce Type: new Abstract: LLM inference is increasingly deployed at institution-scale edges to meet service requirements. However, multi-GPU inference consumes a large amount of electricity and produces substantial heat. To improve sustainability, operators and regulations often demand raising th…

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arXiv Distributed Computing

RoofLang: Enabling AI-Driven Architecting of LLM Inference Systems

arXiv:2609.12551v1 Announce Type: new Abstract: AI is beginning to make substantive contributions to LLM inference optimization. Existing AI optimizations are predominantly profiling-based. Profiling-bound feedback confines the search to the capabilities and performance of an existing software stack, preventing a fund…

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arXiv Distributed Computing

Throughput per Megabyte: A Pilot Benchmark of Language-Stack Efficiency for Self-Hosted HTTP Services on a Raspberry Pi 5

arXiv:2609.11932v1 Announce Type: cross Abstract: Cloud-centric web benchmarks miss constraints that matter for self-hosted services on ARM64 single-board computers, especially idle RAM footprint and energy per request. We ran a pilot benchmark on one Raspberry Pi 5, measuring equivalent SQLite-backed CRUD APIs implem…

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