Due to the complex geometry and physical models of real-world engineering applications, the parallel performance of the mainstream computational fluid dynamics(CFD) codes is unsatisfactory. For complex fluids, an extr...
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ISBN:
(纸本)9781728176505
Due to the complex geometry and physical models of real-world engineering applications, the parallel performance of the mainstream computational fluid dynamics(CFD) codes is unsatisfactory. For complex fluids, an extra stress tensor governed by constitutive equations including nine components brings much more amount of computations. This paper focused on optimizing the most compute-intensive part of a simulation for complex fluids: the iterative linear solver for solving multicomponent equations. Based on the most widely used opensource CFD code OpenFOAM, we unrolled the component loops and replaced the blocking collective MPI calls to non-blocking communications. After operation rescheduling between the loops, the collective communications could be partly overlapped by the computations. Taking the preconditioned conjugate gradient (PCG) algorithm for instance, we presented the complete loop unrolled algorithm for solving multi-component equations. The numerical experiments showed 8.0%~29.0% simulation time reduction for a demonstrative case with 2 million cells on 64~2048 cores. It is worth noting that the approach proposed in this paper is a high-level scheduling algorithm and could be used in combination with other intra-component optimization algorithms, e.g. the pipelined CG methods.
Data-oriented attacks, where the adversary corrupts critical program data in memory, remain one of the most challenging security threats to address. Because the attacker does not touch any code or code pointers, data-...
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ISBN:
(数字)9781665403924
ISBN:
(纸本)9781665403931
Data-oriented attacks, where the adversary corrupts critical program data in memory, remain one of the most challenging security threats to address. Because the attacker does not touch any code or code pointers, data-oriented attacks are able to circumvent common defence strategies such as data execution prevention or control-flow protection. Dataflow integrity (DFI) techniques can mitigate these attacks by detecting corruption of any program data. However, due to highperformance costs, these techniques are not widely adopted in practice. This paper presents TRUVIN, a lightweight scheme that addresses data-oriented attacks by focusing on only those variables which are crucial to the integrity assurance. Instead of checking every memory operation, TRUVIN selectively instruments program data originating from only trusted agents (e.g., the programmer), as they are considered critical to the runtime integrity. Our scheme analyses the program at compile time, and generates instrumentation only for the necessary operations. TRUVIN reduces the performance cost by a factor of 4.3 on average with 28% overhead compared to full instrumentation (121%), while retaining the security guarantees.
At present, there are many excellent genome compression algorithms with high genome compression ratio. However, there is a lack of highly efficient compression algorithms for simultaneous compression of a large number...
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Vehicle-based crowdsensing (VCS) is a special case in crowdsourcing, and task assignment is a basic and important problem. In this paper, we investigate the minimum cost task assignment (MCTA) problem for vehicle-base...
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Aiming at the problem of malicious data deletion or tampering in the untrusted server-side storage, an improved PDP (Provable Data Possession) algorithm supporting privacy protection and multiple copies is proposed in...
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A vital issue regarding hardware implementations of machine learning algorithms with novel memristive devices is the concern of the proposed architecture's resilience to high device variability. We find that most ...
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ISBN:
(数字)9781665415521
ISBN:
(纸本)9781665415538
A vital issue regarding hardware implementations of machine learning algorithms with novel memristive devices is the concern of the proposed architecture's resilience to high device variability. We find that most algorithms have surprisingly high tolerance to variable weight updates and initializations. We also propose a simple method to validate Single Layer Perceptron (SLP) neuromorphic hardware based on memristive RRAM crossbar arrays by studying accuracy vs. training time. Finally, we show high level simulations of an RRAM cell with intermediate states, decay, and Gaussian variability.
We and others have shown that machine learning can detect and mitigate web-based attacks and the propagation of malware. highperformance machine learning frameworks exist for the major computer languages used to prog...
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At present, due to the small size, high power density, high efficiency, a variety of switching power supply is getting more and more widely used. With the improvement of automation degree of power system, especially t...
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The space-terrestrial information network integrates the characteristics of satellite networks and terrestrial networks and can support diversified space network requirements, which has also become a new trend in futu...
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ISBN:
(纸本)9781728176505
The space-terrestrial information network integrates the characteristics of satellite networks and terrestrial networks and can support diversified space network requirements, which has also become a new trend in future network development. In the process of coordinated transmitting between space and terrestrial, satellite may generate a data flow with a set of tasks to be processed while transmitting. Because of the dynamic changes in the links between nodes in the satellite network, how to effectively place the tasks will be huge challenges. In this paper, we considere the traffic changes brought about by task processing, the effectiveness of links, and combined with the operation laws of satellite network and have studied the placement of tasks in dynamic transmitting and processing scenarios. First, we formulate the Task Placement In Dynamic Transmitting-Processing (TPDTP) problem, and then divide the problem into three parts: flow path selection, task allocation between planes, and task placement within plane. For flow path selection, we proposed the Waiting-Time Reducing Path Select (WTRPS) algorithm. For the task allocation problem between planes, we proposed the Time-Constrained Task Placement (TCTP) algorithm and Waiting-Time Utilization Task Placement(WTUTP) algorithm. Finally, we propose Intra-plane Task Placement (IPTP) algorithm to solve the problem of task placement within plane which comprehensive consider the changes in traffic rate and the processing performance of nodes. We evaluate the proposed algorithms using simulations and present evaluation results to show the effectiveness of our design.
A computer code for analyzing the safety feature of triso coated particles for high temperature reactor has been developed based on PANAMA code. This python based code were separated into several modules to perform th...
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A computer code for analyzing the safety feature of triso coated particles for high temperature reactor has been developed based on PANAMA code. This python based code were separated into several modules to perform the main TRIAC-BATAN and linear interpolation calculation, to read the input data file, and to control the sequence of all TRIAC-BATAN calculation. In this initial development phase, TRIAC-BATAN can produce similar pattern as PANAMA calculation in the case of failure fraction of triso particles, either for Depressurized Loss Of Forced Cooling (DLOFC), 100 degrees C higher than DLOFC temperature and constant accident temperature at 1600 degrees C. By using the euclidean distance, TRIAC-BATAN calculation and PANAMA for DLOFC condition are separated in around 3.23.10(-7).
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