the proceedings contain 35 papers. the topics discussed include: dynamic job scheduling on heterogeneous clusters;throughput optimization for micro-factories subject to failures;multi-hop congestion control algorithm ...
ISBN:
(纸本)9780769536804
the proceedings contain 35 papers. the topics discussed include: dynamic job scheduling on heterogeneous clusters;throughput optimization for micro-factories subject to failures;multi-hop congestion control algorithm in mobile wireless networks;a dynamic model for fire emergency evacuation based on wireless sensor networks;CPU load prediction model for distributedcomputing;event-driven configuration of a neural network CMP system over a homogeneous interconnect fabric;parallel position weight matrices algorithms;coarse-grained loop parallelization: iteration space slicing vs affine transformations;on the performance of contention managers for complex transactional memory benchmarks;distributed causal model-based diagnosis based on interacting behavioral Petri Nets;programming abstractions and toolchain for dataflow multithreading architectures;and distributed shared memory for the cell broadband engine (DSMCBE).
the proceedings contain 161 papers. the topics discussed include: deep learning for phishing detection;a partition matching method for optimal attack path analysis;an energy and robustness adjustable optimization meth...
ISBN:
(纸本)9781728111414
the proceedings contain 161 papers. the topics discussed include: deep learning for phishing detection;a partition matching method for optimal attack path analysis;an energy and robustness adjustable optimization method of file distribution services;deriving the political affinity of twitter users from their followers;on the usability of big (social) data;re-running large-scale parallel programs using two nodes;predicting hacker adoption on darkweb forums using sequential rule mining;an on-the-fly scheduling strategy for distributed stream processing platform;deadlock-free adaptive routing based on the repetitive turn model for 3D network-on-chip;and radix: enabling high-throughput georeferencing for phenotype monitoring over voluminous observational data.
the popularity of cloud computing has revolutionized Online Analytical Processing (OLAP), yet risks of privacy leakage limit the use of public clouds in security-critical scenarios, such as healthcare and finance. Ful...
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Transformer-based models are widely used in natural language processing tasks, and their application has been further extended to computer vision as well. In their usage, data security has become a crucial concern whe...
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Transformer-based models are widely used in natural language processing tasks, and their application has been further extended to computer vision as well. In their usage, data security has become a crucial concern when deploying deep learning services on cloud platforms. To address these security concerns, Multi-party computation (MPC) is employed to prevent data and model leakage during the inference process. However, Transformer model introduces several challenges for MPC computation, including the time overhead of the Softmax (normalized exponential) function, the accuracy issue caused by the "dynamic range" of approximated division and exponential, and the high memory overhead when processing long sequences. To overcome these challenges, we propose MLformer, an MPC-based inference framework for transformer models based on Crypten Knott et al. (Adv Neural Inf Process Syst 34: 4961-4973, 2021), a secure machine learning framework suggested by Facebook AI Research group, in the semi-honest adversary model. In this framework, we replace the softmax attention with linear attention, which has linear time and memory complexity with input length. the modification eliminates the softmax function entirely, resulting in lower time and memory overhead. To ensure the accuracy of linear attention, we propose the scaled linear attention to address the dynamic range issue caused by the MPC division used and a new approximate division function is proposed to reduce the computational time of the attention block. Furthermore, to improve the efficiency and accuracy of MPC exponential and reciprocal which are commonly used in transformer model, we propose a novel MPC exponential protocol and first integrate the efficient reciprocal protocol Bar-Ilan and Beaver (in Proceedings of the 8th annual ACM symposium on principles of distributedcomputing, pp. 201-209, 1989) to our framework. Additionally, we optimize the computation of causal linear attention, which is utilized in private in
the proceedings contain 79 papers. the topics discussed include: message dissemination under the multicasting communication mode;e-science in the cloud with CARMEN;exploring biocomplexity: new challenges for high perf...
ISBN:
(纸本)0769530494
the proceedings contain 79 papers. the topics discussed include: message dissemination under the multicasting communication mode;e-science in the cloud with CARMEN;exploring biocomplexity: new challenges for high performance computing;multiprocessor scheduling for distance constrained task systems;task allocation in distributed embedded systems by genetic programming;distant-based resource placement in product networks;monitoring employees' emails without violating their privacy right;email categorization using multi-stage classification technique;a trap-door method for subscription-based mobile content;improved genetic algorithms and list scheduling techniques for independent task scheduling in distributed systems;a remote memory swapping system for cluster computers;a distributed approach for negotiating resource contributions in dynamic collaboration;and performance evaluation of a novel CMP cache structure for hybrid workloads.
Microprocessor design space exploration is an inevitable stage in the early stages of microprocessor design. In work [1], a critical path analysis based design space exploration method is proposed. Critical path analy...
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ISBN:
(纸本)9781728111414
Microprocessor design space exploration is an inevitable stage in the early stages of microprocessor design. In work [1], a critical path analysis based design space exploration method is proposed. Critical path analysis on the instruction dependence graph is often used in the research of the micro-architecture of the instruction pipeline of the microprocessor. Previous analysis method must process the huge log file serially and the analysis time was very long. In this paper, a parallel analysis algorithm based on multithreading was presented. By partitioning the log file into multiple blocks and using multiple threads to process them in parallel, this algorithm achieved a nearly linear speedup according to the number of thread.
this paper proposes a DNA computing model to calculate both inversion and division over finite field GF(2(n)). It is designed based on the previous works by combining modular-multiplication into the process of computi...
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ISBN:
(纸本)9781728111414
this paper proposes a DNA computing model to calculate both inversion and division over finite field GF(2(n)). It is designed based on the previous works by combining modular-multiplication into the process of computing inversion. It adds the function of computing division comparing withthe previous model of inversion. the computation tiles performing 9 different functions assemble into the seed configuration with inputs to figure out the result. this model requires 6857 types of computation tiles and 11 types of boundary tiles.
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