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Fair and efficient coflow scheduling improves application-level networking performance in today's datacenters. Ideally, a coflow scheduler should provide isolation guarantees on the minimum coflow progress to achieve predictable networking performance. Network operators, on the other hand, strive to decrease the average coflow completion time (CCT). Unfortunately, optimal isolation guarantees and...
Link utilization has received extensive attention since datacenters become the most prevalent platform for data-parallel computing applications. A specific job of such applications involves communication among multiple machines. The coflow abstraction depicts such communication and captures application performance through corresponding network requirements. Existing techniques to improve link utilization,...
A green pyrolysis approach to prepare ultra-small nitrogen and sulfur-co-doped carbon dots (N,S-C-dots, QY reaches 55.7%) with precursors citric acid (CA) as carbon source and N-acetyl-l-cysteine as N and S dopant has been explored. The optical properties and the origin of photoluminescence (PL) have been investigated at length. The mixed excitation independence character (200 ≤ λex ≤ 380 nm) and...
Despite of the importance of enantiomers, the fluorescence sensing of enantiomers and the interpretation of the “preferential interaction” still remain insufficiently explored. In this study, we report the recognition of tyrosine (Tyr) enantiomers by chiral N-acetyl-L-cysteine (L-NAC) capped CdSe/CdS quantum dots (QDs) under alkaline experimental condition. L-Tyr could greatly quench the fluorescence...
Data-parallel applications, especially those associated with user-facing web services, have struggled to enhance their worst case performance. It is therefore important to improve the minimum amount of resources guaranteed for applications in a cluster. Existing cluster management frameworks, however, provide isolation for computation resources (such as CPU) only, and are oblivious to network isolation...
With the advent of big data processing frameworks, the performance of data-parallel applications is heavily affected by the time it takes to read input data, making it important to improve data locality. Existing methods in achieving data locality have primarily focused on selecting machines to place tasks of applications. Nevertheless, the set of machines that an application can choose from is determined...
Tasks in a data-parallel job communicate with each other through a number of concurrent flows, which is described as a coflow. These flows are correlated in the sense that the performance of a coflow is dictated by the flow that takes the longest time to complete. Minimizing coflow completion times, however, turns out to be a challenge, given the correlation across flows and how they are routed collectively...
Guaranteed performance for data-parallel applications is important for both service providers and cloud data centers that host such services. A job of data-parallel applications involves communication among multiple machines to transmit intermediate results. Such communication comprises a collection of parallel flows, which is abstracted as a coflow in recent proposals. In this paper, we study the...
Even with the recent proliferation of in-memory computation in data-parallel frameworks (such as Spark), transfers over the network are still time-consuming. Similar to computation, network transfers serve as main roadblocks as we try to minimize job completion times. Existing schedulers were designed as isolated solutions that focused on computation or network performance only. Without any coordination,...
Nitrogen (N), oxygen (O) and phosphorus (P) decorated porous carbon (PC) is in situ synthesized for supercapacitors by H3PO4 activation of shrimp shell. The results show that shrimp shell with 5.32wt% nitrogen, 30.1wt% carbon and 40.2wt% oxygen is a good carbon precursor, and H3PO4 plays an important role on the formation of porous structure and P doping. The contents of N, O and P functional groups...
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