145 research outputs found
Adaptive CPU Resource Allocation for Emulator in Kernel-based Virtual Machine
The technologies of heterogeneous multi-core architectures, co-location, and
virtualization can be used to reduce server power consumption and improve
system utilization, which are three important technologies for data centers.
This article explores the scheduling strategy of Emulator threads within
virtual machine processes in a scenario of co-location of multiple virtual
machines on heterogeneous multi-core architectures. In this co-location
scenario, the scheduling strategy for Emulator threads significantly affects
the performance of virtual machines. This article focuses on this thread for
the first time in the relevant field. This article found that the scheduling
latency metric can well indicate the running status of the vCPU threads and
Emulator threads in the virtualization environment, and applied this metric to
the design of the scheduling strategy. This article designed an Emulator thread
scheduler based on heuristic rules, which, in coordination with the host
operating system's scheduler, dynamically adjusts the scheduling scope of
Emulator threads to improve the overall performance of virtual machines. The
article found that in real application scenarios, the scheduler effectively
improved the performance of applications within virtual machines, with a
maximum performance improvement of 40.7%
Effect of 4-nonylphenol on the sperm dynamic parameters, morphology and fertilization rate of Bufo raddei
4-Nonylphenol (NP) is a compound that causes endocrine disruption and affects sperm quality of mammals and fish. However, the effects of NP on the sperm and fertilization rate of amphibians remain unknown. This study investigates the in vivo and in vitro effects of NP on the sperm dynamic parameters and fertilization rate of Bufo raddei during the period of amplexus and fertilization, and proposes the induction of these effects. In in vivo assay, male B. raddei were exposed to 3 concentrations of NP (50, 200, or 400 ÎŒg/l) or alcohol (0.04â°, control) for 1-3 days. The results suggested that effects on NP on the sperm dynamic parameters, sperm integrity and fertilization rate were not significant (p>0.05). In in vitro assay, the sperm of B. raddei was directly exposed to NP. Based on the results, NP significantly affected the sperm dynamic parameters and integrity (p<0.05). Meanwhile, the sperm reactive oxygen species (ROS) level in the sperm increased significantly (p<0.05), and a negative correlation was recorded between sperm motility and its corresponding ROS level (R=â0.90). Besides, fertilization rate was significantly reduced compared with that of control (p<0.01). The sperm membrane was impaired as well. However, a risk that NP can disrupt the reproduction behavior of B. raddei exists, and the ROS induced by NP and NP itself would be associated with the reduction of fertilization.Keywords: 4-Nonylphenol, Bufo raddei, sperm, morphology, fertilizatio
DFlow: Efficient Dataflow-based Invocation Workflow Execution for Function-as-a-Service
The Serverless Computing is becoming increasingly popular due to its ease of
use and fine-grained billing. These features make it appealing for stateful
application or serverless workflow. However, current serverless workflow
systems utilize a controlflow-based invocation pattern to invoke functions. In
this execution pattern, the function invocation depends on the state of the
function. A function can only begin executing once all its precursor functions
have completed. As a result, this pattern may potentially lead to longer
end-to-end execution time. We design and implement the DFlow, a novel
dataflow-based serverless workflow system that achieves high performance for
serverless workflow. DFlow introduces a distributed scheduler (DScheduler) by
using the dataflow-based invocation pattern to invoke functions. In this
pattern, the function invocation depends on the data dependency between
functions. The function can start to execute even its precursor functions are
still running. DFlow further features a distributed store (DStore) that
utilizes effective fine-grained optimization techniques to eliminate function
interaction, thereby enabling efficient data exchange. With the support of
DScheduler and DStore, DFlow can achieving an average improvement of 60% over
CFlow, 40% over FaaSFlow, 25% over FaasFlowRedis, and 40% over KNIX on 99%-ile
latency respectively. Further, it can improve network bandwidth utilization by
2x-4x over CFlow and 1.5x-3x over FaaSFlow, FaaSFlowRedis and KNIX,
respectively. DFlow effectively reduces the cold startup latency, achieving an
average improvement of 5.6x over CFlow and 1.1x over FaaSFlowComment: 22 pages, 13 figure
DiLogics: Creating Web Automation Programs With Diverse Logics
Knowledge workers frequently encounter repetitive web data entry tasks, like
updating records or placing orders. Web automation increases productivity, but
translating tasks to web actions accurately and extending to new specifications
is challenging. Existing tools can automate tasks that perform the same logical
trace of UI actions (e.g., input text in each field in order), but do not
support tasks requiring different executions based on varied input conditions.
We present DiLogics, a programming-by-demonstration system that utilizes NLP to
assist users in creating web automation programs that handle diverse
specifications. DiLogics first semantically segments input data to structured
task steps. By recording user demonstrations for each step, DiLogics
generalizes the web macros to novel but semantically similar task requirements.
Our evaluation showed that non-experts can effectively use DiLogics to create
automation programs that fulfill diverse input instructions. DiLogics provides
an efficient, intuitive, and expressive method for developing web automation
programs satisfying diverse specifications
MARS: Exploiting Multi-Level Parallelism for DNN Workloads on Adaptive Multi-Accelerator Systems
Along with the fast evolution of deep neural networks, the hardware system is
also developing rapidly. As a promising solution achieving high scalability and
low manufacturing cost, multi-accelerator systems widely exist in data centers,
cloud platforms, and SoCs. Thus, a challenging problem arises in
multi-accelerator systems: selecting a proper combination of accelerators from
available designs and searching for efficient DNN mapping strategies. To this
end, we propose MARS, a novel mapping framework that can perform
computation-aware accelerator selection, and apply communication-aware sharding
strategies to maximize parallelism. Experimental results show that MARS can
achieve 32.2% latency reduction on average for typical DNN workloads compared
to the baseline, and 59.4% latency reduction on heterogeneous models compared
to the corresponding state-of-the-art method.Comment: Accepted by 60th DA
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