--- title: JPDC 2025 Digest venue: JPDC year: 2025 date: '2025-01-01' tags: [] paper_count: 12 draft: false --- 12 papers selected. --- ### Throughput of Byzantine Broadcast *Ruomu Hou, Haifeng Yu, Prateek Saxena* **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. **Why notable** — Provides the first rigorous throughput characterization of Byzantine broadcast, a fundamental primitive whose capacity limits were previously unquantified. --- ### How to reduce the number of steps for (multi-valued validated) Byzantine agreement? *Baohan Huang, Haibin Zhang, Chao Liu 0039, Shengli Liu 0001 *et al.** **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. **Why notable** — Step complexity is a fundamental metric for distributed agreement; reducing it has direct implications for consensus latency in blockchains and replicated systems. --- ### Locating a black hole in a dynamic ring *Giuseppe Antonio Di Luna, Paola Flocchini, Giuseppe Prencipe, Nicola Santoro* **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. **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. --- ### Dispersion of mobile robots on directed anonymous graphs *Giuseppe F. Italiano, Debasish Pattanayak, Gokarna Sharma* **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. **Why notable** — Directed anonymous graphs model asymmetric communication networks; the dispersion problem's resolution here advances the theory of autonomous distributed agents. --- ### QPOPSS: Query and Parallelism Optimized Space-Saving for finding frequent stream elements *Victor Jarlow, Charalampos Stylianopoulos, Marina Papatriantafilou* **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. **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. --- ### A parallel algorithm for minimum weight set cover with small neighborhood property *Yingli Ran, Yaoyao Zhang, Zhao Zhang 0002* **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. **Why notable** — Expands the frontier of problems admitting efficient parallel approximation, with implications for distributed network optimization where local structure can be exploited. --- ### Optimizing parallel heterogeneous system efficiency: Dynamic task graph adaptation with recursive tasks *Nathalie Furmento, Abdou Guermouche, Gwenolé Lucas, Thomas Morin *et al.** **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. **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. --- ### A scheduler to foster data locality for GPU and out-of-core task-based linear algebra applications *Maxime Gonthier, Loris Marchal, Samuel Thibault* **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. **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. --- ### Leveraging Multi-Instance GPUs through moldable task scheduling *Jorge Villarrubia, Luis Costero, Francisco D. Igual, Katzalin Olcoz* **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. **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. --- ### Integration framework for online thread throttling with thread and page mapping on NUMA systems *Janaina Schwarzrock, Hiago Mayk G. de A. Rocha, Arthur Francisco Lorenzon, Samuel Xavier de Souza *et al.** **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. **Why notable** — Thread throttling and NUMA placement are typically managed independently; their joint online optimization yields measurable gains that neither technique alone achieves. --- ### To repair or not to repair: Assessing fault resilience in MPI stencil applications *Roberto Rocco, Elisabetta Boella, Daniele Gregori, Gianluca Palermo* **TL;DR** — Systematically evaluates the cost-benefit trade-off between full fault recovery and partial resilience strategies for MPI stencil computations under process failures. **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. --- ### A lightweight RDMA connection protocol based on post-hoc confirmation *Ke Wu 0003, Dezun Dong, Weixia Xu 0001* **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. **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.