In this research, we tackled the complex task of aligning audio and lyrics content automatically. This task entails the precise matching of lyrics with the corresponding audio segments in songs, necessitating the coor...
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Traditionally, electricity generation was localized, with a single power plant supplying power to surrounding towns and using only fossil fuels, but as modernization began, increasing electricity demand meant many Bla...
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The proceedings contain 134 papers. The topics discussed include: TailGuard: tail latency SLO guaranteed task scheduling for data-intensive user-facing applications;smart contract parallel execution with fine-grained ...
ISBN:
(纸本)9798350339864
The proceedings contain 134 papers. The topics discussed include: TailGuard: tail latency SLO guaranteed task scheduling for data-intensive user-facing applications;smart contract parallel execution with fine-grained state accesses;DeAR: accelerating distributed deep learning with fine-grained all-reduce pipelining;a game of NFTs: characterizing NFT wash trading in the Ethereum blockchain;uncovering vulnerabilities in Wasm smart contracts;TransOff: towards fast transferable computation offloading in MEC via embedded reinforcement learning;FedDM: data and model heterogeneity-aware federated learning via dynamic weight sharing;state-aware unsafe driving action detection and defense;fair DNN model selection in edge AI via a cooperative game approach;and servo: increasing the scalability of modifiable virtual environments using serverless computing.
Infrastructures usually suffer environmental perturbations, and most of them are low probability events with catastrophic consequences, which poses a challenge to targeted preparedness for the possibility of cascading...
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Dataset Distillation (DD) is a technique for synthesizing smaller, compressed datasets from large original datasets while retaining essential information to maintain efficacy. Efficient DD is a current research focus ...
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ISBN:
(纸本)9798400704369
Dataset Distillation (DD) is a technique for synthesizing smaller, compressed datasets from large original datasets while retaining essential information to maintain efficacy. Efficient DD is a current research focus among scholars. Squeeze, Recover and Relabel ((SReL)-L-2) and Adversarial Prediction Matching (APM) are two advanced and efficient DD methods, yet their performance is moderate with lower volumes of distilled data. This paper proposes an ingenious improvement method, distributed Boosting (DB), capable of significantly enhancing the performance of these two algorithms at low distillation volumes, leading to DB-(SReL)-L-2 and DB-APM. Specifically, DB is divided into three stages: Distribute&Encapsulate, Distill, and Integrate&Mix-relabel. DB-(SReL)-L-2, compared to (SReL)-L-2, demonstrates performance improvements of 25.2%, 26.9%, and 26.2% on full 224x224 ImageNet-1k at Images Per Class (IPC) 10, CIFAR-10 at IPC 10, and CIFAR-10 at IPC 50, respectively. Meanwhile, DB-APM, in comparison to APM, exhibits performance enhancements of 21.2% and 20.9% on CIFAR-10 at IPC 10, CIFAR-100 at IPC 1, respectively. Additionally, we provide a theoretical proof of convergence for DB. To the best of our knowledge, DB is the first method suitable for distributedparallelcomputing scenarios.
Checkpointing (or snapshotting) a system's state has always been a problem of great interest and has found a lot of use in ensuring system reliability, record-replay debugging, job migration and running high-throu...
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ISBN:
(纸本)9798350383225
Checkpointing (or snapshotting) a system's state has always been a problem of great interest and has found a lot of use in ensuring system reliability, record-replay debugging, job migration and running high-throughput transaction systems. In the last few years ultra-fast hardware-assisted NVM-based checkpointing schemes have come up that can collect incremental full-system checkpoints in milliseconds. Unfortunately, such systems have large overheads in terms of their write amplification (increased number of writes). This, in turn, seriously reduces the reliability and lifetime of NVM devices. We propose the first tunable scheme in this space, JASS, where given a checkpoint latency (CL), we near-optimally minimize the write amplification (WA). This allows us to run parallel programs in a disciplined fashion. To realize this goal, we propose many novel hardware along the way such as a rigorous method of flushing pre-checkpoint messages in the NoC, a novel DRAM scrubber and locality predictor, and a control-theoretic algorithm to guarantee a CL while minimizing the WA. We reduce WA by 35-96% as compared to the nearest state-of-the-art competing method and improve performance of PARSEC benchmarks by 19.4%.
In the electric distribution grid, the access of distributed electric power generation also brings new technical challenges. From the perspective of operation, after the distributed generation is related to the electr...
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The authors have been conducting research and development on VG-Hub (Virtual grid Hub) as a device to configure a distributed power source that utilizes renewable energy by integrating and cooperatively feeding power ...
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ISBN:
(纸本)9784907626525
The authors have been conducting research and development on VG-Hub (Virtual grid Hub) as a device to configure a distributed power source that utilizes renewable energy by integrating and cooperatively feeding power from small-scale storage batteries and power-generating devices such as solar panels. While the previous system allows for the configuration of power flow according to user-selected scenarios, the control to change the settings of each port of the VG-Hubs composing the network is a sequential process, and reducing the number of control cycles has been an issue. In this study, we address this issue as a constrained combinatorial optimization problem and report a method to reduce the number of control step cycles using Fixstars Amplify, a cloud platform for running quantum annealing machines, along with its fundamental evaluation.
The embedded real-time system not only pays attention to the correctness of software task function, but also pays attention to the correctness of software task timing. There are a lot of IO resources in embedded real-...
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In light of recent advancements in Internet of Multimedia Things (IoMT) and 5G technology, both the variety and quantity of data have been rapidly increasing. Consequently, handling zero-shot cross-modal retrieval (ZS...
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