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检索条件"任意字段=21st International Symposium on Computer Architecture and High Performance Computing"

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An Automata-Theoretic Approach to Synthesizing Binarized Neural Networks 21st

An Automata-Theoretic Approach to Synthesizing Binarized Ne...

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21st international symposium on Automated Technology for Verification and Analysis, ATVA 2023

作者： Tao, Ye Liu, Wanwei Song, Fu Liang, Zhen Wang, Ji Zhu, Hongxu College of Computer Science and Technology National University of Defense Technology Changsha China School of Information Science and Technology ShanghaiTech University Shanghai China Institute of Software Chinese Academy of Sciences and University of Chinese Academy of Sciences Beijing China Automotive Software Innovation Center Shanghai China Institute for Quantum Information and State Key Laboratory for High Performance Computing National University of Defense Technology Changsha China

ISBN: (纸本)9783031453281

Deep neural networks, (DNNs, a.k.a. NNs), have been widely used in various tasks and have been proven to be successful. However, the accompanied expensive computing and storage costs make the deployments in resource-constrained devices a significant concern. To solve this issue, quantization has emerged as an effective way to reduce the costs of DNNs with little accuracy degradation by quantizing floating-point numbers to low-width fixed-point representations. Quantized neural networks (QNNs) have been developed, with binarized neural networks (BNNs) restricted to binary values as a special case. Another concern about neural networks is their vulnerability and lack of interpretability. Despite the active research on trustworthy of DNNs, few approaches have been proposed to QNNs. To this end, this paper presents an automata-theoretic approach to synthesizing BNNs that meet designated properties. More specifically, we define a temporal logic, called BLTL, as the specification language. We show that each BLTL formula can be transformed into an automaton on finite words. To deal with the state-explosion problem, we provide a tableau-based approach in real implementation. For the synthesis procedure, we utilize SMT solvers to detect the existence of a model (i.e., a BNN) in the construction process. Notably, synthesis provides a way to determine the hyper-parameters of the network before training. Moreover, we experimentally evaluate our approach and demonstrate its effectiveness in improving the individual fairness and local robustness of BNNs while maintaining accuracy to a great extent. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Deep neural networks

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Enforcing delay-aware fog-cloud based IoT firewall (Work In Progress)

Enforcing delay-aware fog-cloud based IoT firewall (Work In ...

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IEEE international symposium on Network computing and Applications

作者： Towhidul Islam Asif Ahmed Tanvir Raihan Rezwana Reaz Department of CSE Bangladesh University of Engineering and Technology Bangladesh

ISBN: (纸本)9798350397314

Firewalls for IoT devices can be enforced at the gateway or at the cloud. Utilizing a fog based architecture, firewalls can also be enforced at fog layer. Depending on where the firewall is running, varying delays and overhead will be experienced by IoT devices. Some IoT devices are sensitive to the incurred delays. So choosing the most suitable platform to enforce firewall for each individual device under the different load conditions is important. In this work, we present a delay-aware IoT firewall enforcing mechanism using fog-cloud based architecture.

关键词： Firewalls (computing) computer architecture Logic gates Delays Internet of Things

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A high-Speed HBM Receiver Design for high-performance computing Systems

A High-Speed HBM Receiver Design for High-Performance Comput...

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international SoC Design Conference, ISOCC

作者： Thinh Nguyen-Viet Gyung-Su Byun Department of Electrical and Computer Engineering Inha University Incheon Korea

ISBN: (数字)9798350377088

ISBN: (纸本)9798350377095

In this paper, we present a receiver design that achieves high data rates while maintaining low power consumption for high bandwidth memory (HBM) applications, using 28-nm CMOS technology. The proposed receiver scheme incorporates an analog front-end with an active inductor and wide-range peaking control, effectively compensating for the significant losses from heavy capacitive loading in a multi-stack through-silicon-via (TSV) I/O channel at a low supply voltage of 0.7 V. Simulation results indicate that the receiver can process data at a rate of 11 Gb/s, consuming 1.15 mW of power in a 1 pF, 12-stacked HBM configuration. Additionally, the proposed receiver achieves an energy efficiency of 0.104 pJ/b/pF, demonstrating its potential for enhancing HBM system performance.

关键词： Active inductors high performance computing System performance Loading Receivers Bandwidth CMOS technology Energy efficiency Through-silicon vias Voltage control

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Multi-objective Deep Reinforcement Learning for Mobile Edge computing

Multi-objective Deep Reinforcement Learning for Mobile Edge ...

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international symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

作者： Ning Yang Junrui Wen Meng Zhang Ming Tang Institute of Automation Chinese Academy of Sciences Beijing China ZJU-UIUC Institute Zhejiang University Zhejing China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China

Mobile edge computing (MEC) is essential for next-generation mobile network applications that prioritize various performance metrics, including delays and energy consumption. However, conventional single-objective scheduling solutions cannot be directly applied to practical systems in which the preferences of these applications (i.e., the weights of different objectives) are often unknown or challenging to specify in advance. In this study, we address this issue by formulating a multi-objective offloading problem for MEC with multiple edges to minimize expected long-term energy consumption and transmission delay while considering unknown preferences as parameters. To address the challenge of unknown preferences, we design a multi-objective (deep) reinforcement learning (MORL)-based resource scheduling scheme with proximal policy optimization (PPO). In addition, we introduce a well-designed state encoding method for constructing features for multiple edges in MEC systems, a sophisticated reward function for accurately computing the utilities of delay and energy consumption. Simulation results demonstrate that our proposed MORL scheme enhances the hypervolume of the Pareto front by up to 233.1% compared to benchmarks.

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Cloud-Native Plinth: A Platform to Support Containerized 5G Core Networks

Cloud-Native Plinth: A Platform to Support Containerized 5G ...

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IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems (MASS)

作者： Shen Gao Shuo Quan Jie Wu Cloud Computing Research Institute China Telecom Beijing P.R. China

ISBN: (数字)9798350363999

ISBN: (纸本)9798350364002

With the proliferation of 5G Core (5GC) network workloads, the cloudification of 5GC has emerged as a pre-dominant trend. Cloud-native technologies enhance the carrier cloud of 5GC by providing capabilities for rapid recovery, agility, elasticity, and scalable service access. Beyond the management and orchestration systems, it is imperative to deploy several other common services to fully realize the advantages of cloud-native environments. In this paper, we propose Cloud-Native Plinth (CNP), a collection of cloud-native services built on the Platform as a Service (PaaS) layer to support the deployment of containerized 5GC. Within the architecture of CNP, specific services essential for the operation of containerized Virtual Network Functions (VNFs) are delineated. These services are implemented through Cloud-Native computing Foundation (CNCF) projects and are tailored to the unique requirements of 5GC. Furthermore, the introduction of CNP not only facilitates the deployment of containerized 5GC but also enhances its high availability, performance, and reliability.

关键词： Cloud computing 5G mobile communication Scalability Platform as a service computer architecture Smart systems Reliability engineering Market research Security Optimization

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An Analytical Bound for Choosing Trivial strategies in Co-scheduling 21st

An Analytical Bound for Choosing Trivial Strategies in Co-sc...

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21st international Conference on Computational Science and Its Applications (ICCSA)

作者： Kuchumov, Ruslan Korkhov, Vladimir St Petersburg State Univ 7-9 Univ Skaya Nab St Petersburg 199034 Russia

ISBN: (纸本)9783030870102;9783030870096

Efficient usage of shared high-performance computing (HPC) resources raises the problem of HPC applications co-scheduling, i.e. the problem of execution of multiple applications simultaneously on the same shared computing nodes. Each application may have different requirements for shared resources (e.g. network bandwidth or memory bus bandwidth). When these resources are used concurrently, their resource throughputs may decrease, which leads to performance degradation. In this paper we define application behavior model in co-scheduling environment and formalize a scheduling problem. Within the model we evaluate trivial strategies and compare them with an optimal strategy. The comparison provides a simple analytical criteria for choosing between a naive strategy of running all applications in parallel or any sophisticated strategies that account for applications performance degradation.

关键词： high performance computing Co-scheduling Scheduling theory Linear programming

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Infinite Virtual Space Exploration Using Space Tiling and Perceivable Reset at Fixed Positions 21

Infinite Virtual Space Exploration Using Space Tiling and Pe...

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21st IEEE international symposium on Mixed and Augmented Reality (ISMAR)

作者： Kwon, Soon-Uk Jeon, Sang-Bin Hwang, June-Young Cho, Yong-Hun Park, Jinhyung Lee, In-Kwon Yonsei Univ Dept Comp Sci Seoul South Korea

ISBN: (数字)9781665453257

ISBN: (纸本)9781665453257

A simultaneous walking experience in virtual and real spaces can provide a high sense of presence. However, users may face challenges when walking within a large virtual space while walking in a small and complex real space. Several methods such as Redirected Walking (RDW) and Substitutional Reality (SR) have been proposed as different approaches to this problem. However, the users must "reset" their movement direction at unpredictable moments to avoid collision in a small and complex real space when using subtle RDW that does not maintain the correspondence between virtual and real space. Contrarily, exploration through the SR has a limitation in that the VR scene is restricted to a controlled area. In this paper, we propose Reset at Fixed Positions (RFP), a method that combines RDW with the advantage of the SR and matches walkable real space with walkable virtual space. To utilize RFP, we defined Guaranteed Space Block (GSB), a unit space that constitutes a walkable virtual space. This space is obtained through the point reflection of the GSB utilizing the reset position within the GSB. RFPs can be implemented by two methods: Generating Virtual Space Using RFP (G-RFP) and Implementing Given Virtual Space Using RFP (I-RFP). G-RFP can create an infinitely large virtual space for exploration. On the other hand, I-RFP can configure a given virtual environment to make users walk. We observed that G-RFP provides higher presence, immersion and a higher mean distance traveled between resets compared to the existing RDW method in a complex real space through a user study. In addition, exploration through I-RFP provided a higher immersion, a comparable presence, and a similar number of resets.

关键词： Human-centered computing Human computer interaction (HCI) Interaction paradigms Virtual reality computing methodologies computer graphics Graphics systems and interfaces Perception Virtual reality

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Data Poisoning Attack to X-armed Bandits 21

Data Poisoning Attack to X-armed Bandits

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21st IEEE international Conference on Trust, Security and Privacy in computing and Communications, TrustCom 2022

作者： Luo, Zhi Li, Youqi Chen, Lixing Xu, Zichuan Zhou, Pan Huazhong University of Science and Technology School of Cyber Science and Engineering China Beijing Institute of Technology School of Cyberspace Science and Technology School of Computer Science China Shanghai Jiao Tong University Institute of Cyber Science and Technology China Dalian University of Technology School of Software China Huazhong University of Science and Technology Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering China

ISBN: (纸本)9781665494250

X-armed bandits have achieved the state-of-the-art performance in optimizing unknown stochastic continuous functions, which can model many machine learning tasks, specially in big data-driven personalized recommendation. However, bandit algorithms are vulnerable to adversarial attacks. Existing works mainly focus on attacking multi-armed bandits in discrete setting;nevertheless, the attacks against X-armed bandits in continuous setting have not been well explored. In this paper, we aim to bridge this gap and investigate the robustness problem for the X-armed bandits. Specifically, we consider data poisoning attack and propose an attack algorithm named Confidence Poisoning Attack algorithm, which could hijack the clean tree-based X-armed bandits algorithm, i.e., high confidence tree (HCT) and make it choose the nodes including the arm targeted by the attacker very frequently with a sub-linear attack cost, i.e., O(Tα)(0 © 2022 IEEE.

关键词： stochastic systems

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Tender: Accelerating Large Language Models via Tensor Decomposition and Runtime Requantization

Tender: Accelerating Large Language Models via Tensor Decomp...

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Annual international symposium on computer architecture, ISCA

作者： Jungi Lee Wonbeom Lee Jaewoong Sim Department of Electrical and Computer Engineering Seoul National University

ISBN: (数字)9798350326581

ISBN: (纸本)9798350326598

Large language models (LLMs) demonstrate outstanding performance in various tasks in machine learning and have thus become one of the most important workloads in today’s computing landscape. However, deploying LLM inference poses challenges due to the high compute and memory requirements stemming from the enormous model size and the difficulty of running it in the integer pipelines. In this paper, we present Tender, an algorithm-hardware co-design solution that enables efficient deployment of LLM inference at low precision. Based on our analysis of outlier values in LLMs, we propose a decomposed quantization technique in which the scale factors of decomposed matrices are powers of two apart. The proposed scheme allows us to avoid explicit requantization (i.e., dequantization/quantization) when accumulating the partial sums from the decomposed matrices, with a minimal extension to the commodity tensor compute hardware. Our evaluation shows that Tender achieves higher accuracy and inference performance compared to the state-of-the-art methods while also being significantly less intrusive to the existing accelerators.

关键词： Quantization (signal) Tensors Runtime Large language models Computational modeling Scalability Hardware

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Constructing Hardware Accelerators for Number-Theoretic Transform Using high-Level Synthesis

Constructing Hardware Accelerators for Number-Theoretic Tran...

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international SoC Design Conference, ISOCC

作者： Hyeri Roh Woo-Seok Choi Department of Electrical and Computer Engineering ISRC Seoul National University Seoul Korea

ISBN: (数字)9798350377088

ISBN: (纸本)9798350377095

The rapid advancements in quantum computing threaten traditional public-key cryptosystems, necessitating the development of quantum-safe cryptographic solutions like post-quantum cryptography and lattice-based cryptography. However, the widespread adoption of these technologies is hindered by the computational intensity of operations such as polynomial multiplication over rings. Although the Number Theoretic Transform (NTT) is used to speed up the polynomial multiplication, but it remains the main bottleneck in terms of latency. This paper presents an NTT accelerator that utilizes memory bank division and high-level synthesis with pipelining techniques in a 28nm CMOS process. The proposed accelerator supports a wide range of polynomial degree, reduces latency by a factor of up to 7.2, and minimizes area by a factor of 2.8-5.1 compared to prior art.

关键词： Privacy Quantum computing Memory architecture Transforms CMOS process Public key cryptography Polynomials Cryptography Hardware acceleration Pipeline processing

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