scholarly journals Effect of Regulation on the Increasing Price of Metals and Minerals to Meet the Challenges in Clean Energy Transitions: A Case Study of China

2022 ◽  
Vol 14 (2) ◽  
pp. 764
Author(s):  
Lin Xu ◽  
Zhenwei Guo
Keyword(s):  
High Performance ◽  
Clean Energy ◽  
Global Scale ◽  
Fair Price ◽  
Critical Metals ◽  
Consumer Country ◽  
Critical Metal ◽  
Metal Support ◽  
Performance Computing

Considering that the development of science and technology depends on metal support, the EU, USA, and China have issued a critical metal list on the development report. However, the scarce and important mineral deposits on a global scale will not be enough to meet the huge needs of economic development in the future. Many fields such as renewable energy, high-performance computing, and AI all require critical metals as essential supports. A proper price regulation of such important metals will contribute to the fair price power on the international market. In this paper, the pricing history and strategy of critical metal support are fully studied and discussed. Since China has become a major consumer country, China should gain fair price power in the market of important metals.

Hardware Accelerator Integration Tradeoffs for High-Performance Computing: A Case Study of GEMM Acceleration in N-Body Methods

2021 ◽  
Vol 32 (8) ◽  
pp. 2035-2048
Author(s):  
Mochamad Asri ◽  
Dhairya Malhotra ◽  
Jiajun Wang ◽  
George Biros ◽  
Lizy K. John ◽  
...  
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Hardware Accelerator ◽  
Performance Computing

scholarly journals Log Analysis-Based Resource and Execution Time Improvement in HPC: A Case Study

2020 ◽  
Vol 10 (7) ◽  
pp. 2634
Author(s):  
JunWeon Yoon ◽  
TaeYoung Hong ◽  
ChanYeol Park ◽  
Seo-Young Noh ◽  
HeonChang Yu
Keyword(s):  
Execution Time ◽  
High Performance ◽  
Large Scale ◽  
Experimental Result ◽  
Optimization Approach ◽  
Root Cause ◽  
Large Systems ◽  
Job Scheduler ◽  
Performance Computing

High-performance computing (HPC) uses many distributed computing resources to solve large computational science problems through parallel computation. Such an approach can reduce overall job execution time and increase the capacity of solving large-scale and complex problems. In the supercomputer, the job scheduler, the HPC’s flagship tool, is responsible for distributing and managing the resources of large systems. In this paper, we analyze the execution log of the job scheduler for a certain period of time and propose an optimization approach to reduce the idle time of jobs. In our experiment, it has been found that the main root cause of delayed job is highly related to resource waiting. The execution time of the entire job is affected and significantly delayed due to the increase in idle resources that must be ready when submitting the large-scale job. The backfilling algorithm can optimize the inefficiency of these idle resources and help to reduce the execution time of the job. Therefore, we propose the backfilling algorithm, which can be applied to the supercomputer. This experimental result shows that the overall execution time is reduced.

Improvement in Server Compute Performance Using Advanced Air Cooled Thermal Solutions

2017 ◽  
Author(s):  
Devdatta Kulkarni ◽  
Sandeep Ahuja ◽  
Sanjoy Saha
Keyword(s):  
Form Factor ◽  
Boundary Conditions ◽  
High Performance ◽  
Thermal Design ◽  
Air Cooling ◽  
Liquid Cooling ◽  
Increasing Demand ◽  
Performance Computing ◽  
Design Power

Continuously increasing demand for higher compute performance is pushing for improved advanced thermal solutions. In high performance computing (HPC) area, most of the end users deploy some sort of direct or indirect liquid cooling thermal solutions. But for the users who have air cooled data centers and air cooled thermal solutions are challenged to cool next generation higher Thermal Design Power (TDP) processors in the same platform form factor without changing environmental boundary conditions. This paper presents several different advanced air cooled technologies developed to cool high TDP processors in the same form factor and within the same boundary conditions of current generation processor. Comparison of thermal performance using different cooling technologies such as Liquid Assist Air Cooling (LAAC) and Loop Heat Pipe (LHP) are presented in this paper. A case study of Intel’s Knights Landing (KNL) processor is presented to show case the increase in compute performance due to different advanced air cooling technologies.

scholarly journals A Case Study of Quantizing Convolutional Neural Networks for Fast Disease Diagnosis on Portable Medical Devices

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 219
Author(s):  
Mukhammed Garifulla ◽  
Juncheol Shin ◽  
Chanho Kim ◽  
Won Hwa Kim ◽  
Hye Jung Kim ◽  
...  
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Medical Devices ◽  
Energy Efficient ◽  
High Performance ◽  
Medical Image Analysis ◽  
Disease Diagnosis ◽  
Mobile System ◽  
Performance Computing

Recently, the amount of attention paid towards convolutional neural networks (CNN) in medical image analysis has rapidly increased since they can analyze and classify images faster and more accurately than human abilities. As a result, CNNs are becoming more popular and play a role as a supplementary assistant for healthcare professionals. Using the CNN on portable medical devices can enable a handy and accurate disease diagnosis. Unfortunately, however, the CNNs require high-performance computing resources as they involve a significant amount of computation to process big data. Thus, they are limited to being used on portable medical devices with limited computing resources. This paper discusses the network quantization techniques that reduce the size of CNN models and enable fast CNN inference with an energy-efficient CNN accelerator integrated into recent mobile processors. With extensive experiments, we show that the quantization technique reduces inference time by 97% on the mobile system integrating a CNN acceleration engine.

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