The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carb...The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carbon dioxide(CO_2) and store methane(CH4), where the latter is a kind of clean energy source with abundant reserves and lower CO_2 emission. Hundreds of thousands of porous materials can be enrolled on the candidate list, but how to quickly identify the really promising ones, or even evolve materials(namely, rational design high-performing candidates) based on the large database of present porous materials? In this context, high-throughput computational techniques, which have emerged in the past few years as powerful tools, make the targets of fast evaluation of adsorbents and evolving materials for CO_2 capture and CH_4 storage feasible. This review provides an overview of the recent computational efforts on such related topics and discusses the further development in this field.展开更多
In recent years, the advent of emerging computing applications, such as cloud computing, artificial intelligence, and the Internet of Things, has led to three common requirements in computer system design： high utili...In recent years, the advent of emerging computing applications, such as cloud computing, artificial intelligence, and the Internet of Things, has led to three common requirements in computer system design： high utilization, high throughput, and low latency. Herein, these are referred to as the requirements of ＇high-throughput computing （HTC）＇. We further propose a new indicator called ＇sysentropy＇ for measuring the degree of chaos and uncertainty within a computer system. We argue that unlike the designs of traditional computing systems that pursue high performance and low power consumption, HTC should aim at achieving low sysentropy. However, from the perspective of computer architecture, HTC faces two major challenges that relate to （1） the full exploitation of the application＇s data parallelism and execution concurrency to achieve high throughput, and （2） the achievement of low latency, even in the cases at which severe contention occurs in data paths with high utilization. To overcome these two challenges, we introduce two techniques： on-chip data flow architecture and labeled von Neumann architecture. We build two prototypes that can achieve high throughput and low latency, thereby significantly reducing sysentropy.展开更多
基金supported by the Natural Science Foundation of China (Nos.21706106,21536001 and 21322603)the National Key Basic Research Program of China ("973") (No.2013CB733503)+1 种基金the Natural Science Foundation of Jiangsu Normal University(16XLR011)Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘The globally increasing concentrations of greenhouse gases in atmosphere after combustion of coal-or petroleum-based fuels give rise to tremendous interest in searching for porous materials to efficiently capture carbon dioxide(CO_2) and store methane(CH4), where the latter is a kind of clean energy source with abundant reserves and lower CO_2 emission. Hundreds of thousands of porous materials can be enrolled on the candidate list, but how to quickly identify the really promising ones, or even evolve materials(namely, rational design high-performing candidates) based on the large database of present porous materials? In this context, high-throughput computational techniques, which have emerged in the past few years as powerful tools, make the targets of fast evaluation of adsorbents and evolving materials for CO_2 capture and CH_4 storage feasible. This review provides an overview of the recent computational efforts on such related topics and discusses the further development in this field.
基金Project supported by the National Key R&D Program of China(No.2016YFB1000201)the National Natural Science Foundation of China(No.61420106013)the Youth Innovation Promotion Association of Chinese Academy of Sciences
文摘In recent years, the advent of emerging computing applications, such as cloud computing, artificial intelligence, and the Internet of Things, has led to three common requirements in computer system design： high utilization, high throughput, and low latency. Herein, these are referred to as the requirements of ＇high-throughput computing （HTC）＇. We further propose a new indicator called ＇sysentropy＇ for measuring the degree of chaos and uncertainty within a computer system. We argue that unlike the designs of traditional computing systems that pursue high performance and low power consumption, HTC should aim at achieving low sysentropy. However, from the perspective of computer architecture, HTC faces two major challenges that relate to （1） the full exploitation of the application＇s data parallelism and execution concurrency to achieve high throughput, and （2） the achievement of low latency, even in the cases at which severe contention occurs in data paths with high utilization. To overcome these two challenges, we introduce two techniques： on-chip data flow architecture and labeled von Neumann architecture. We build two prototypes that can achieve high throughput and low latency, thereby significantly reducing sysentropy.
