Hash is one of the most important algorithms of cryptography, it is widely used in cryptographic primitives, such as digital signature, key exchange and so on. Further, hash cryptography is also the core operation of ...
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ISBN:
(纸本)9781665473156
Hash is one of the most important algorithms of cryptography, it is widely used in cryptographic primitives, such as digital signature, key exchange and so on. Further, hash cryptography is also the core operation of blockchain technology. With the explosive growth of the number of IoT devices and the rapid development of blockchain technology, the computing performance of hash has received widespread attention. The GPU high-performance computing platforms with a number of arithmetic cores are widely used in cryptographic optimization and acceleration. In this paper, we propose an efficient parallel accelerated framework of SM3 cryptography hash function based on GPU parallel computing devices, short for GPU-based SM3 (G-SM3). Our G-SM3 optimizes the implementation of the hash cryptographic algorithm from three aspects: parallelism, memory access and instructions. On the desktop GPU NVIDIA Titan V, the peak performance of G-SM3 reaches 23 GB/s, which is more than 7.5 times the performance of OpenSSL on a top-level server CPU (E5-2699V3) with 16 cores. On the embedded GPU which consumes less than 40 W, the SM3 throughput reaches 3.8 GB/s, which is even better than the performance of the server-level CPU. Based on the same GTX 1080, our performance is 1.12 times that of the fastest known GPU implementation, and the latency is reduced by more than 95%. Compared to other platforms, our G-SM3 has a huge advantage.
Aiming to address the data security issues in data sharing, current approaches such as RBAC, ABAC, and blockchain-based data sharing platforms suffer from problems like role redundancy, role abuse, complex authorizati...
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More and more renewable energy sources are being integrated into the electricity grid as a result of the quick advancement in distributed generation technology and the in-fluence of government support policies. Integr...
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The proceedings contain 11 papers. The topics discussed include: Oruga: an avatar of representational systems.theory;cognitive analysis for representation change;an overview of the ABC repair system for datalog-like t...
The proceedings contain 11 papers. The topics discussed include: Oruga: an avatar of representational systems.theory;cognitive analysis for representation change;an overview of the ABC repair system for datalog-like theories;repairing numerical equations in analogically blended theories using reformation;experiments in learning Dyck-1 languages with recurrent neural networks;integrating paraphrasing into the frank QA system;the handshake problem for human-like coordination systems.extending an embodied cognitive architecture with spatial representation and reasoning;prediction: an algorithmic principle meeting neuroscience and machine learning halfway;explanations from deep reinforcement learning using episodic memories;the computational gauntlet of human-like learning 59Pat Langley;and representing and processing emotions in a cognitive architecture.
A large quantity of statistics is generated each day using DevOps techniques from many sources;inclusive of sensors, internet site utilization, gadget activities, and so on. This sparkling waft of activities have to b...
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The decrease in fossil fuel reserves has prompted a global move towarddistributed energy resources. For this reason, solar PV power generation has recently gained much attention as a feasible renewable energy source....
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The article considers an assessment of the possibility to improve the reliability of electric network operation with in-grid microgeneration facilities (small generating units based on renewable energy sources) throug...
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The industrial Internet can be seen as a combination of industrial software, sensors, networks and cloud platforms. Among them, industrial software is the key to data utilization while the cloud platform provides supp...
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Federated Average algorithm (FEDAVG) is the preferred algorithm for federated learning (FL) because of its simplicity and low communication cost However, if all clients39;s local data aren39;t independent and equa...
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Virtual power plants can help active distribution networks fully utilize and efficiently manage large amounts of distributed energy resources by calculating the aggregate flexibility of VPPs at the point of common cou...
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