A focused digest of distributed computing, cloud-native infrastructure, and engineering research from authoritative sources.
arXiv:2609.04478v1 Announce Type: new Abstract: Confidential serverless computing is rapidly emerg- ing as a critical paradigm for application domains requiring strong confidentiality guarantees, such as healthcare, finance, and machine learning. To enable this paradigm in untrusted cloud environments, Confidential Vi…
Read at sourcearXiv:2609.04513v1 Announce Type: new Abstract: Compound AI workflows are increasingly used to serve complex AI tasks by coordinating multiple AI models and software components. This approach enables deployment flexibility, as each workflow stage can expose different model variants and resource requirements, but it al…
Read at sourcearXiv:2609.04547v1 Announce Type: new Abstract: As an increasing number of embedded platforms incorporate multiple processing units, shared resource contention induced unpredictable execution time poses a challenge for real-time system design. Memory bandwidth regulation is a popular mitigation approach, and MemGuard…
Read at sourcearXiv:2609.04573v1 Announce Type: new Abstract: Exascale simulations generate data far faster than it can be stored or analyzed, making efficient data reduction essential. Error-controlled lossy compression offers high compression ratios under user-specified error bounds, but the target tolerance must be fixed at comp…
Read at sourcearXiv:2609.04609v1 Announce Type: new Abstract: In training Mixture-of-Experts (MoE) models, sharded data parallelism partitions each expert's parameters across GPUs, requiring an Allgather operation to reconstruct the full weight matrix before each layer executes. This communication often dominates iteration time. Pr…
Read at sourcearXiv:2609.04952v1 Announce Type: new Abstract: Distributed DNN inference is increasingly deployed in containerized edge-cloud environments, where workloads run on-device or are exposed to remote clients over the network. Accurate online power estimation on resource-constrained ARM nodes without hardware power counter…
Read at sourcearXiv:2506.04061v1 Announce Type: cross Abstract: Modern nanofabrication techniques have enabled us to manipulate the wavefront of light with sub-wavelength-scale structures, offering the potential to replace bulky refractive surfaces in conventional optics with ultrathin metasurfaces. In theory, arrays of nanoposts p…
Read at sourcearXiv:2609.04382v1 Announce Type: cross Abstract: We present a systems-security case study of a two-node split-LLM training system whose privacy evaluation passed while leaving an observable channel untested. The Trusted Local Node (TLN) sends protected activations to the Untrusted Cloud Node (UCN), the UCN returns it…
Read at sourcearXiv:2609.04397v1 Announce Type: cross Abstract: Modern atomistic simulations increasingly employ localized orbitals to represent quantum operators, yielding sparse block matrices whose block shapes vary with chemical species and basis choice. Conventional scalar sparse formats store the entries of each block individ…
Read at sourcearXiv:2609.04417v1 Announce Type: cross Abstract: Distributed AI training involves recurring rounds of data exchange between multiple pairs of GPU nodes. Slowdown in even one flow due to congestion can cause the entire communication round to slowdown. Current approaches for evading congestion in AI clusters assume glo…
Read at sourcearXiv:2609.04524v1 Announce Type: cross Abstract: Distributed quantum computing (DQC) offers a promising approach to scale quantum computing by overcoming the resource limitations of a single quantum processor. However, inter-node communication remains a major bottleneck of DQC due to inefficient and error-prone entan…
Read at sourcearXiv:2609.04663v1 Announce Type: cross Abstract: Modern CPUs increasingly integrate high-throughput matrix engines optimized for low-precision AI workloads, while many scientific computing applications still rely on FP32 and FP64 GEMM to meet their numerical accuracy requirements. This mismatch motivates an algorithm…
Read at sourcearXiv:2609.04748v1 Announce Type: cross Abstract: Prefix caching, in which a serving engine reuses the key and value tensors of a shared prompt prefix across requests, is enabled by default in the major open-source stacks and treated as a transparent optimization. We measure what it costs in reproducibility, and find…
Read at sourcearXiv:2609.04763v1 Announce Type: cross Abstract: Due to resource constraints or external and internal uncertainties, clients in real-world federated learning systems are often intermittently available edge devices. In highly dynamic environments, the parameter server lacks prior real-time knowledge of clients' availa…
Read at sourcearXiv:2609.05012v1 Announce Type: cross Abstract: Federated scientific machine learning enables institutions to train neural surrogates without centralizing local physical data, yet studies of partial differential equations (PDEs) lack a transferable definition of non-independent and identically distributed data. Exis…
Read at sourcearXiv:2609.05406v1 Announce Type: cross Abstract: Grid studies often represent data-center flexibility as a fixed percentage of load, although no public production trace has shown how much eligible load persists across event durations or co-moves across clusters. We reconstruct 4,439 hourly power observations from a 1…
Read at sourcearXiv:2606.29629v3 Announce Type: replace Abstract: Multimodal model inference creates substantial energy demand with growing performance requirements. Within GPUs, power is autonomously managed by an on-board power management unit (PMU), which makes frequency boosting/throttling decisions. However, we find that these…
Read at sourcearXiv:2608.18029v2 Announce Type: replace Abstract: A popular class of Byzantine fault-tolerant atomic broadcast protocols rely on directed acyclic graphs (DAGs) that represent causal relations between broadcast messages. Each process applies a protocol-specific \emph{commit rule} on its local DAG to determine which v…
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