Kubernetes 1.37 is here and Dynamic Resource Allocation (DRA) keeps pushing past where it started! This release brings DRA Extended Resource support to GA, a milestone the team has been building toward for three straight releases. Several more features graduate to Beta or GA. A fresh batch of alpha features rounds out…
There’s still time to join OSPOlogy + OSPO Summit China 2026, taking place on September 7, 2026, in Shanghai, China as part of KubeCon + CloudNativeCon + OpenInfra Summit + PyTorch Conference China. This event will...
Somewhere in your cluster there’s probably a deployment sitting in the default namespace that everyone knows shouldn’t be there. Nobody put it there maliciously, it just happened, early on, before anyone had opinions about namespace hygiene,...
arXiv:2609.01821v1 Announce Type: new Abstract: With the rise of inference as today's dominant AI workload, the industry is transitioning to high-bandwidth photonic interconnects to meet the large scale-up requirements of increasingly complex Mixture-of-Experts (MoE) models. This paper quantifies the benefits of 3D-in…
arXiv:2609.01864v1 Announce Type: new Abstract: NVIDIA distributed shared memory (DSMEM) enables direct shared-memory access within a thread block cluster. However, cluster synchronization, remote access, and resource costs make it difficult to determine when DSMEM improves performance. To fill this gap, we propose CR…
arXiv:2609.01975v1 Announce Type: new Abstract: Recent GPU generations include special-purpose ray tracing (RT) cores for graphics applications. While RT cores are primarily used for rendering, recent works show they can be leveraged for general-purpose tasks, including similarity searches. However, existing approache…
arXiv:2609.02109v1 Announce Type: new Abstract: Deploying heterogeneous AI models concurrently on a shared GPU introduces resource contention that complicates runtime scheduling. While surrogate models avoid costly online benchmarking, their profiling requirements typically grow combinatorially with the number of co-r…
arXiv:2609.02227v1 Announce Type: new Abstract: Genome-wide association studies (GWAS) gain statistical power from large, ancestrally diverse cohorts, but privacy regulations and data-residency constraints often prevent genomic data from being centrally pooled across institutional or national borders. We present a pri…
arXiv:2609.02238v1 Announce Type: new Abstract: The American Science Cloud (AmSC), established under the Genesis Mission of the U.S. Department of Energy (DOE), aims to integrate DOE high-performance computing systems, experimental facilities, and data resources into a single, coordinated, AI-driven discovery platform…
arXiv:2609.02514v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) on edge devices typically relies on model compression or split inference. However, compression degrades reasoning capabilities, while split inference suffers from severe Wide Area Network (WAN) communication bottlenecks. Edge-cloud…
arXiv:2609.00275v1 Announce Type: cross Abstract: Fleets of LLM agents now externalize effects that cannot be fully undone: they move money, deploy code, delete data, and disclose information. Current controls check one effect at a time, so a fleet of individually authorized agents can overdraw its principal's risk un…
arXiv:2609.01939v1 Announce Type: cross Abstract: Autonomous agent runtimes execute tool actions that mutate databases, repositories, and cloud services across organizational boundaries. Authorization and local compensation cover pre-action admission and in-runtime rollback, but neither settles the residual harm left…
arXiv:2609.02450v1 Announce Type: cross Abstract: Semantic triggers in federated learning (FL) can be less conspicuous than synthetic patches, but sample-dependent placement may weaken backdoor implantation across aggregation rounds. This challenge is compounded in decentralized FL (DFL), where topology-dependent peer…
arXiv:2609.02736v1 Announce Type: cross Abstract: Semiconductor quantum-dot arrays are a compelling platform for scalable quantum technologies, yet their practical operation is hindered by the complexity of tuning large-scale devices. Existing automation tools rely on simplified physical models---such as constant-capa…
arXiv:2609.02866v1 Announce Type: cross Abstract: Revocation completion, clean state, or operation success can leave authorized work able to cause an effect the application rejects while the provider stays within its contract. We call the absence of all such paths policy-relative effect closure, or effect closure for…
arXiv:2609.02876v1 Announce Type: cross Abstract: Ordinary differential equations (ODEs) underlie models in science and engineering, and many applications need derivatives of their solutions with respect to parameters. Ensembles of independent trajectories suit graphics processing units (GPUs), but current GPU softwar…
arXiv:2509.23722v3 Announce Type: replace Abstract: Pipeline parallelism is widely used to train large language models (LLMs). However, increasing heterogeneity in model architectures exacerbates pipeline bubbles, thereby reducing training efficiency. Prior approaches typically optimize a single phase of the pipeline…
arXiv:2510.21549v3 Announce Type: replace Abstract: The distributed coloring problem is arguably one of the key problems studied in the area of distributed graph algorithms. The most standard variant of the problem asks for a proper vertex coloring of a graph with $\Delta + 1$ colors, where $\Delta$ is the maximum deg…