https://column.distributedcomputegrid.com/A focused digest of distributed computing, cloud-native infrastructure, and engineering research from authoritative sources.enWed, 02 Sep 2026 13:59:39 +0000https://www.cncf.io/blog/2026/09/02/metal3-meets-kubevirtbmc-provisioning-kubevirt-vms-like-bare-metal/https://www.cncf.io/blog/2026/09/02/metal3-meets-kubevirtbmc-provisioning-kubevirt-vms-like-bare-metal/Wed, 02 Sep 2026 11:31:00 +0000CNCFIn the previous post , we introduced KubeVirtBMC and showed how it provides virtual BMC endpoints for KubeVirt VMs. We tested it with raw IPMI and Redfish commands. That was fun, but the real power of...https://arxiv.org/abs/2609.00205https://arxiv.org/abs/2609.00205Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.00205v1 Announce Type: new Abstract: The growing scale of scientific data makes lossy compression essential for reducing data volume under controllable error. Transformation-based compressors using multilevel decomposition, such as MGARD, achieve strong compression ratios but map poorly to GPU architectures…https://arxiv.org/abs/2609.00392https://arxiv.org/abs/2609.00392Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.00392v1 Announce Type: new Abstract: Leader-based consensus datastores (etcd, ZooKeeper) face two competing routing goals: spread load evenly across members, and route operations to the member whose protocol role matches the operation. Writes must commit through the leader, so sending them elsewhere adds a…https://arxiv.org/abs/2609.00400https://arxiv.org/abs/2609.00400Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.00400v1 Announce Type: new Abstract: High-energy physics analyses often process the same data as physicists refine algorithms and test new ideas. With data increasingly read from remote storage, each iteration is subject to network latency and depends on network bandwidth and shared-storage throughput, whic…https://arxiv.org/abs/2609.00442https://arxiv.org/abs/2609.00442Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.00442v1 Announce Type: new Abstract: Large language model (LLM) services increasingly process heterogeneous queries with diverse latency, accuracy, and resource requirements. While edge deployment reduces response time, the heterogeneity of devices and the diversity of model families, parameter scales, and…https://arxiv.org/abs/2609.00561https://arxiv.org/abs/2609.00561Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.00561v1 Announce Type: new Abstract: In the application of incomplete Cholesky preconditioning to the incomplete Cholesky-conjugate gradient (ICCG) method, forward and backward substitutions exhibit sequential dependencies that constitute a major bottleneck for parallelization in multicore environments. To…https://arxiv.org/abs/2609.00817https://arxiv.org/abs/2609.00817Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.00817v1 Announce Type: new Abstract: Characterising AI workload performance on modern HPC systems requires understanding both their scalability in isolation and their behaviour under concurrent execution. However, the interplay among parallelisation strategies, network congestion, compute capability, and in…https://arxiv.org/abs/2609.00837https://arxiv.org/abs/2609.00837Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.00837v1 Announce Type: new Abstract: In blockchain systems, transaction order directly determines financial outcomes: unfair ordering enables front-running and sandwich attacks that have extracted over \$686M from Ethereum users. Current fair-ordering protocols aggregate pairwise receive-order evidence from…https://arxiv.org/abs/2609.00843https://arxiv.org/abs/2609.00843Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.00843v1 Announce Type: new Abstract: We study unstable integer sorting on GPUs for arrays whose elements lie in a known integer range. Focusing on counting-sort-based methods that determine the output interval of each value from its frequency and the prefix sums of the frequencies, we propose and evaluate R…https://arxiv.org/abs/2609.00877https://arxiv.org/abs/2609.00877Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.00877v1 Announce Type: new Abstract: Edge platforms instantiate executable services close to users to reduce request-serving cost, but each instance incurs a one-time deployment cost and remains useful only for a finite time-to-live (TTL). The resulting online decision is both prediction-sensitive and capac…https://arxiv.org/abs/2609.00993https://arxiv.org/abs/2609.00993Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.00993v1 Announce Type: new Abstract: Rollout inference often dominates the wall-clock time of large-scale reinforcement learning (RL). In agentic RL, each trajectory alternates between model generation and environment interaction over multiple turns. Asynchronous trajectories consequently introduce new pref…https://arxiv.org/abs/2609.01025https://arxiv.org/abs/2609.01025Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.01025v1 Announce Type: new Abstract: Density Functional Theory (DFT) is indispensable for materials science and drug discovery, yet the exchange--correlation (XC) evaluation remains a major bottleneck due to its cubic scaling. Although linear-scaling methods exploit electronic nearsightedness to reduce asym…https://arxiv.org/abs/2609.01082https://arxiv.org/abs/2609.01082Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.01082v1 Announce Type: new Abstract: In an edge--cloud collaborative edge-computing environment, an edge node (EN) must decide whether each user task should be executed locally, forwarded to a remote service (or cloud) node (SN), or rejected. The EN observes its local state directly but receives the SN stat…https://arxiv.org/abs/2609.01457https://arxiv.org/abs/2609.01457Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.01457v1 Announce Type: new Abstract: Large language model (LLM) fine-tuning is increasingly shifting toward data generated on edge devices, where memory, computation, bandwidth, and connectivity constraints make conventional federated learning difficult to sustain. Split federated fine-tuning (SFT) improves…https://arxiv.org/abs/2609.01490https://arxiv.org/abs/2609.01490Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.01490v1 Announce Type: new Abstract: This work considers the multidimensional approximate agreement problem. In this problem, $n$ parties in a distributed system, up to $t$ of which may be corrupted by a Byzantine adversary, need to output vectors that are close to each other and that lie inside the convex…https://arxiv.org/abs/2609.00227https://arxiv.org/abs/2609.00227Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.00227v1 Announce Type: cross Abstract: LLM agents increasingly diagnose incidents and propose remediations. In a GitOps workflow, applying a fix means editing a version-controlled config file, and the obvious implementation, having the model author the edited file or a diff, is what practitioners reach for…https://arxiv.org/abs/2609.00406https://arxiv.org/abs/2609.00406Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.00406v1 Announce Type: cross Abstract: Distributed deployment runtimes carry a coherence obligation that classical fault-tolerance frameworks do not name directly: the live state a component is configured to run and the audit chain that records how it got there must agree at every terminal configuration. Pr…https://arxiv.org/abs/2609.00659https://arxiv.org/abs/2609.00659Wed, 02 Sep 2026 04:00:00 +0000arXiv Distributed ComputingarXiv:2609.00659v1 Announce Type: cross Abstract: Cooperative perception allows a drone fleet to combine observations from multiple viewpoints. However, existing systems typically fix their feature-sharing policies at design time or adapt to only one context signal. This is a poor fit for aerial fleets, whose missions…