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2,978 papers
A load-aware GPU-based dynamic graph pattern matching scheme is proposed to make full use of GPU computing resources and a task overhead prediction model is proposed to guide task allocation to alleviate the load imbalance between multiple GPU devices.
With the growing deployment of intelligent applications in the Internet of Vehicles (IoV), collaborative deep neural network (DNN) inference across edge nodes has become essential for satisfying real-time processing and service demands. As a key enabler for 6G networks, rate-splitting multiple access (RSMA) offers impr...
Through bypassing the long-distance transmission of cloud services, Mobile Edge Computing (MEC) reduces response delay and ensures Quality-of-Service (QoS). In resource-constrained MEC, due to the strong coupling between service provisioning and task execution, reasonable service caching and resource allocation face ma...
With the development of UAV communications and aerial edge intelligence, Uncrewed Aerial Vehicles (UAVs) are increasingly used for inspection in high-risk environments. However, limited onboard energy and data-privacy constraints make efficient collaborative learning challenging. Hierarchical Federated Learning (HFL) p...
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Regarding the computational intensity and stringent latency requirements of modern applications comprised of many dependent subtasks, collaborative edge computing (CEC) emerges as a solution to guarantee the service-level objectives (SLOs) by offloading subtasks to multiple distributed edge servers. However, existing o...
Multi-tenant computing, which executes multiple neural networks on a single GPU, is essential for maximizing hardware utilization in both cloud and edge environments. However, effective co-location faces a fundamental trade-off between utilization and safety. On one hand, the diverse computing patterns of concurrent mo...
Nano-size-induced shifts in alloy phase-separation critical temperatures (TCnano) are investigated by introducing an atomistic concept of site-specific contributions to the shift (SSCS) associated with different atomic coordination environments in cuboctahedral and truncated-octahedral nanoparticles (NPs). TCnano previ...
A dynamic vertical scaling strategy based on Proximal Policy Optimization, formulated as a Partially Observable Markov Decision Process, which jointly adjusts task allocations and prioritizes compliance with a p95 end-to-end latency Service Level Objective is presented.
The sCXR demonstrated image quality characteristics that were generally comparable to conventional chest radiography in several of the categories under investigation, highlighting the potential of sCXR as a companion image with the added flexibility of generating multiple projection views.
In this article, we compute the Hilbert series of the generalized binomial edge ideal associated with the join of two graphs. Consequently, we compute the Hilbert series of complete $r$-partite graphs. Further, we show that if a vertex satisfies a certain degree condition, then some Hilbert coefficients remain unchange...
This paper implements HeatCache atop vLLM and shows that it reduces computing energy by up to 18.0%, decreases thermal-throttle exposure by 81.7%, and maintains SLO violation rates below 0.9% even up to $48~^{\circ}\mathrm{C}$.
NovaFabric is presented, producing audit-grade execution evidence: provider-neutral, tamper-evident, replayable, shareable and conditional on a stated trusted computing base.
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
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For decades, a fundamental question about the difficulty of computing in high-dimensional spaces has resisted proof. New research resolves this question, removing a major theoretical obstacle to understanding the efficiency of randomized algorithms used across science and computing. The Kannan–Lovász–Simonovits (KLS) conjecture was proposed in 1995. It asks whether, for a broad class of high-dimensional […] The post Solving a 31-year-old grand challenge in mathematics – the KLS conjecture appear…
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
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