79 research outputs found
HL-Pow: A Learning-Based Power Modeling Framework for High-Level Synthesis
High-level synthesis (HLS) enables designers to customize hardware designs
efficiently. However, it is still challenging to foresee the correlation
between power consumption and HLS-based applications at an early design stage.
To overcome this problem, we introduce HL-Pow, a power modeling framework for
FPGA HLS based on state-of-the-art machine learning techniques. HL-Pow
incorporates an automated feature construction flow to efficiently identify and
extract features that exert a major influence on power consumption, simply
based upon HLS results, and a modeling flow that can build an accurate and
generic power model applicable to a variety of designs with HLS. By using
HL-Pow, the power evaluation process for FPGA designs can be significantly
expedited because the power inference of HL-Pow is established on HLS instead
of the time-consuming register-transfer level (RTL) implementation flow.
Experimental results demonstrate that HL-Pow can achieve accurate power
modeling that is only 4.67% (24.02 mW) away from onboard power measurement. To
further facilitate power-oriented optimizations, we describe a novel design
space exploration (DSE) algorithm built on top of HL-Pow to trade off between
latency and power consumption. This algorithm can reach a close approximation
of the real Pareto frontier while only requiring running HLS flow for 20% of
design points in the entire design space.Comment: published as a conference paper in ASP-DAC 202
Bronchoscopic ethanol injection combined with cryotherapy is an effective treatment for benign airway stenosis caused by endotracheal intubation or tracheotomyc
The benign tracheal stenosis is a challenge in interventional pulmonary disease. Bronchoscopic ethanol injection (BEI) is always used in airway stenosis caused by malignant tracheal tumor. The efficacy and safety of BEI in benign airway stenosis has not been studied before. To compare the safety and efficacy between bronchoscopic icryotherapy and BEI combined with bronchoscopic cryotherapy in the treatment of benign tracheal stenosis. A retrospective study included 61 patients with tracheal stenosis caused by endotracheal intubation and tracheotomy from July 2010 to June 2015 was made. 33 patients received repeated bronchoscopic cryotherapy alone were in Group A, 29 patients underwent repeated cryotherapy combined with BEI were in Group B. Dyspnea index, tracheal diameter were collected before and after treatment. Efficacy and complications were compared in two groups. The changes of tracheal diameter, dyspnea index were significant before and after treatment in both groups (P < 0.05). The long-term cure rate was higher in group B than that in group A (100% vs 84.8%). The average duration for dilated airway stable was much shorter in group B than group A (166±28 days vs 278±32 days, P < 0.05). The average cryotherapy session performed in group B was significantly less than that in group A (22.1±4.7 vs 34.9±6.5, P < 0.05). Meanwhile the complications in group A were seldom, the incidence of complications related to BEI were low in group B (mild chest pain 7.1%, bleeding 3.6% and cough 10.7%). BEI combined with bronchoscopic cryotherapy is an effective minimally invasive choice for releasing the airway obstructive symptoms
X-ray emission for 424 MeV/u C ions impacting on selected targets
In inertial Confinement Fusion (ICF), X-ray
radiation drives the implosion requiring not only
sufficient conversion efficiency of the drive
energy to the X-ray but also the highly spatial
symmetry..
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
Validation of the digital health literacy assessment among the university students in China
PurposeWith the development of the internet, digital health literacy (DHL) has become increasingly important for managing health. Consequently, various digital health literacy scales have been created for different groups. The purpose of this study was to verify the reliability and validity of the simplified Chinese version of the Digital Health Literacy Assessment (DHLA) scale among university students in China.MethodSnowball sampling was used to recruit the participants via an online platform (Wenjuan.com), and finally 304 university students were included in the survey. Demographic information and the status of DHL were collected through the online questionnaire. Cronbach’s alpha and split-half reliability were used to test the internal consistency of the scale, while the structural validity was verified by exploratory factor analysis and confirmatory factor analysis. Additionally, the convergence of the scale was tested by composite reliability (CR) and average variance extracted (AVE).ResultTwo dimensions were generated from 10 entries in the scale, named Self-rated Digital Health Literacy and Trust Degree of Online Health Information, respectively. The Cronbach’s alpha and split-half reliability of the total scale were 0.912 and 0.828, while the Cronbach’s alpha of the two dimensions were 0.913 and 0.830, respectively. The structural validity-related indexes of the scale met the standards (RMSEA = 0.079, GFI = 0.943, AGFI = 0.902, CFI = 0.971). In each dimension, the CR and AVE also reached critical values (CR > 0.7 and AVE > 0.5).ConclusionThe scale had high reliability and validity, indicating the simplified Chinese DHLA scale could be used to evaluate the DHL of university students in China
Transport of intense ion beams in plasmas: collimation and energy-loss reduction
We compare the transport properties of a well-characterized hydrogen plasma
for low and high current ion beams. The energy-loss of low current beams can be
well understood, within the framework of current stopping power models.
However, for high current proton beams, significant energy-loss reduction and
collimation is observed in the experiment. We have developed a new
particle-in-cell code, which includes both collective electromagnetic effects
and collisional interactions. Our simulations indicate that resistive magnetic
fields, induced by the transport of an intense proton beam, act to collimate
the proton beam and simultaneously deplete the local plasma density along the
beam path. This in turn causes the energy-loss reduction detected in the
experiment
Anomalous stopping of laser-accelerated intense proton beam in dense ionized matter
Ultrahigh-intensity lasers (10-10W/cm) have opened up new
perspectives in many fields of research and application [1-5]. By irradiating a
thin foil, an ultrahigh accelerating field (10 V/m) can be formed and
multi-MeV ions with unprecedentedly high intensity (10A/cm) in short
time scale (ps) are produced [6-14]. Such beams provide new options in
radiography [15], high-yield neutron sources [16], high-energy-density-matter
generation [17], and ion fast ignition [18,19]. An accurate understanding of
the nonlinear behavior of beam transport in matter is crucial for all these
applications. We report here the first experimental evidence of anomalous
stopping of a laser-generated high-current proton beam in well-characterized
dense ionized matter. The observed stopping power is one order of magnitude
higher than single-particle slowing-down theory predictions. We attribute this
phenomenon to collective effects where the intense beam drives an decelerating
electric field approaching 1GV/m in the dense ionized matter. This finding will
have considerable impact on the future path to inertial fusion energy.Comment: 8 pages, 4 figure
Energy loss enhancement of very intense proton beams in dense matter due to the beam-density effect
Thoroughly understanding the transport and energy loss of intense ion beams
in dense matter is essential for high-energy-density physics and inertial
confinement fusion. Here, we report a stopping power experiment with a
high-intensity laser-driven proton beam in cold, dense matter. The measured
energy loss is one order of magnitude higher than the expectation of individual
particle stopping models. We attribute this finding to the proximity of beam
ions to each other, which is usually insignificant for relatively-low-current
beams from classical accelerators. The ionization of the cold target by the
intense ion beam is important for the stopping power calculation and has been
considered using proper ionization cross section data. Final theoretical values
agree well with the experimental results. Additionally, we extend the stopping
power calculation for intense ion beams to plasma scenario based on Ohm's law.
Both the proximity- and the Ohmic effect can enhance the energy loss of intense
beams in dense matter, which are also summarized as the beam-density effect.
This finding is useful for the stopping power estimation of intense beams and
significant to fast ignition fusion driven by intense ion beams
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