Vincent Lannurien
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133 lines
6.5 KiB
Markdown
133 lines
6.5 KiB
Markdown
---
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title: JPDC 2025 Digest
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venue: JPDC
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year: 2025
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date: '2025-01-01'
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tags: []
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paper_count: 12
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draft: false
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---
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12 papers selected.
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### Throughput of Byzantine Broadcast
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*Ruomu Hou, Haifeng Yu, Prateek Saxena*
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**TL;DR** — Establishes tight throughput bounds for Byzantine broadcast protocols and constructs algorithms that saturate those bounds, separating throughput from latency in the fault-tolerant broadcast landscape.
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**Why notable** — Provides the first rigorous throughput characterization of Byzantine broadcast, a fundamental primitive whose capacity limits were previously unquantified.
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### How to reduce the number of steps for (multi-valued validated) Byzantine agreement?
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*Baohan Huang, Haibin Zhang, Chao Liu 0039, Shengli Liu 0001 *et al.**
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**TL;DR** — Presents new Byzantine agreement protocols that lower the step complexity for multi-valued and validated variants, breaking barriers that have stood since the classical results.
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**Why notable** — Step complexity is a fundamental metric for distributed agreement; reducing it has direct implications for consensus latency in blockchains and replicated systems.
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### Locating a black hole in a dynamic ring
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*Giuseppe Antonio Di Luna, Paola Flocchini, Giuseppe Prencipe, Nicola Santoro*
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**TL;DR** — Solves the black-hole search problem on rings whose topology changes over time, establishing the agent and time complexity of locating a fatal node in a dynamic distributed environment.
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**Why notable** — Extends a classic distributed exploration problem to dynamic graphs, requiring new algorithmic techniques that are broadly applicable to fault detection in evolving networks.
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### Dispersion of mobile robots on directed anonymous graphs
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*Giuseppe F. Italiano, Debasish Pattanayak, Gokarna Sharma*
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**TL;DR** — Characterizes the necessary and sufficient conditions for a group of mobile robots to disperse to distinct nodes of a directed anonymous graph, and provides optimal algorithms.
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**Why notable** — Directed anonymous graphs model asymmetric communication networks; the dispersion problem's resolution here advances the theory of autonomous distributed agents.
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### QPOPSS: Query and Parallelism Optimized Space-Saving for finding frequent stream elements
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*Victor Jarlow, Charalampos Stylianopoulos, Marina Papatriantafilou*
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**TL;DR** — Redesigns the Space-Saving frequent-elements sketch for concurrent shared-memory execution, achieving high query throughput alongside update throughput without sacrificing approximation accuracy.
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**Why notable** — Bridges the gap between approximate streaming data structures and parallel execution, demonstrating that heavy-hitter summaries can scale on multicore without significant accuracy loss.
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### A parallel algorithm for minimum weight set cover with small neighborhood property
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*Yingli Ran, Yaoyao Zhang, Zhao Zhang 0002*
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**TL;DR** — Gives a parallel approximation algorithm for minimum weight set cover instances where sets have bounded neighborhood size, achieving near-optimal approximation ratio in poly-logarithmic rounds.
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**Why notable** — Expands the frontier of problems admitting efficient parallel approximation, with implications for distributed network optimization where local structure can be exploited.
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### Optimizing parallel heterogeneous system efficiency: Dynamic task graph adaptation with recursive tasks
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*Nathalie Furmento, Abdou Guermouche, Gwenolé Lucas, Thomas Morin *et al.**
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**TL;DR** — Extends task-graph runtime systems to support recursive task generation, enabling dynamic adaptation of the task graph structure to improve load balance on heterogeneous CPU-GPU platforms.
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**Why notable** — Recursive task parallelism is essential for divide-and-conquer workloads; integrating it into heterogeneous runtimes closes a major gap in practical parallel programming models.
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### A scheduler to foster data locality for GPU and out-of-core task-based linear algebra applications
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*Maxime Gonthier, Loris Marchal, Samuel Thibault*
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**TL;DR** — Proposes a data-locality-aware scheduler for task-based dense linear algebra that simultaneously manages GPU memory and out-of-core data transfers to minimize data movement.
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**Why notable** — Data movement dominates cost in large linear algebra computations; the scheduler's dual handling of GPU memory and disk I/O makes it practically relevant for exascale workloads.
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### Leveraging Multi-Instance GPUs through moldable task scheduling
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*Jorge Villarrubia, Luis Costero, Francisco D. Igual, Katzalin Olcoz*
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**TL;DR** — Develops a moldable task scheduling framework that dynamically partitions GPU compute across concurrent tasks using NVIDIA's Multi-Instance GPU feature to improve overall throughput.
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**Why notable** — MIG is a critical hardware feature for multi-tenant GPU clusters; this work provides the first scheduling framework that exploits it through principled moldable-task theory.
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### Integration framework for online thread throttling with thread and page mapping on NUMA systems
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*Janaina Schwarzrock, Hiago Mayk G. de A. Rocha, Arthur Francisco Lorenzon, Samuel Xavier de Souza *et al.**
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**TL;DR** — Combines online thread-count throttling with NUMA-aware thread and page placement in a unified runtime framework, adaptively co-optimizing both dimensions to maximize performance.
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**Why notable** — Thread throttling and NUMA placement are typically managed independently; their joint online optimization yields measurable gains that neither technique alone achieves.
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### To repair or not to repair: Assessing fault resilience in MPI stencil applications
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*Roberto Rocco, Elisabetta Boella, Daniele Gregori, Gianluca Palermo*
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**TL;DR** — Systematically evaluates the cost-benefit trade-off between full fault recovery and partial resilience strategies for MPI stencil computations under process failures.
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**Why notable** — Provides practitioners with a principled decision framework for resilience in HPC applications, showing when expensive full recovery is justified versus cheaper degraded-mode execution.
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### A lightweight RDMA connection protocol based on post-hoc confirmation
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*Ke Wu 0003, Dezun Dong, Weixia Xu 0001*
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**TL;DR** — Designs an RDMA connection protocol that defers acknowledgment to post-operation confirmation, drastically reducing connection setup overhead for short-lived high-frequency transfers.
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**Why notable** — RDMA setup latency is a critical bottleneck in disaggregated memory and distributed storage systems; this protocol's approach generalizes to any latency-sensitive fabric.
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