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This paper proposes long-term reliability management for spatial multitasking GPU architectures. Specifically, we focus on electromigration (EM)-induced long-term failure of the GPU's power delivery network. A distributed power delivery network model at functional unit granularity is developed and used for our EM analysis of GPU architectures. We use a recently proposed physics-based EM reliability model and consider the EM-induced time-to-failure at the GPU system level as a reliability resource. For GPU scheduling, we mainly focus on spatial multitasking, which allows GPU computing resources to be partitioned among multiple applications. We find that the existing reliability-agnostic thread block scheduler for spatial multitasking is effective in achieving high GPU utilization, but poor reliability. We develop and implement a long-term reliability-aware thread block scheduler in GPGPU-Sim, and compare it against existing reliability-agnostic scheduler. We evaluate several use cases of spatial multitasking and find that our proposed scheduler achieves up to 30\% improvement in long-term reliability. 

We present Fermi Gamma-ray Burst Monitor (Fermi-GBM) and Swift Burst Alert Telescope (Swift-BAT) searches for gamma-ray/X-ray counterparts to gravitational-wave (GW) candidate events identified during the third observing run of the Advanced LIGO and Advanced Virgo detectors. Using Fermi-GBM onboard triggers and subthreshold gamma-ray burst (GRB) candidates found in the Fermi-GBM ground analyses, the Targeted Search and the Untargeted Search, we investigate whether there are any coincident GRBs associated with the GWs. We also search the Swift-BAT rate data around the GW times to determine whether a GRB counterpart is present. No counterparts are found. Using both the Fermi-GBM Targeted Search and the Swift-BAT search, we calculate flux upper limits and present joint upper limits on the gamma-ray luminosity of each GW. Given these limits, we constrain theoretical models for the emission of gamma rays from binary black hole mergers.

 

Electric vehicle (EV) adoption promises potential air pollutant and greenhouse gas (GHG) reduction co‐benefits. As such, China has aggressively incentivized EV adoption, however much remains unknown with regard to EVs’ mitigation potential, including optimal vehicle type prioritization, power generation contingencies, effects of Clean Air regulations, and the ability of EVs to reduce acute impacts of extreme air quality events. Here, we present a suite of scenarios with a chemistry transport model that assess the potential co‐benefits of EVs during an extreme winter air quality event. We find that regardless of power generation source, heavy‐duty vehicle (HDV) electrification consistently improves air quality in terms of NO₂and fine particulate matter (PM_2.5), potentially avoiding 562 deaths due to acute pollutant exposure during the infamous January 2013 pollution episode (∼1% of total premature mortality). However, HDV electrification does not reduce GHG emissions without enhanced emission‐free electricity generation. In contrast, due to differing emission profiles, light‐duty vehicle (LDV) electrification in China consistently reduces GHG emissions (∼2 Mt CO₂), but results in fewer air quality and human health improvements (145 avoided deaths). The calculated economic impacts for human health endpoints and CO₂reductions for LDV electrification are nearly double those of HDV electrification in present‐day (155M vs. 87M US$), but are within ∼25% when enhanced emission‐free generation is used to power them. Overall, we find only a modest benefit for EVs to ameliorate severe wintertime pollution events, and that continued emission reductions in the power generation sector will have the greatest human health and economic benefits.

 

Abstract The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in 2019 April and lasting six months, O3b starting in 2019 November and lasting five months, and O3GK starting in 2020 April and lasting two weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org . The main data set, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages. 

Abstract We use 47 gravitational wave sources from the Third LIGO–Virgo–Kamioka Gravitational Wave Detector Gravitational Wave Transient Catalog (GWTC–3) to estimate the Hubble parameter H ( z ), including its current value, the Hubble constant H 0 . Each gravitational wave (GW) signal provides the luminosity distance to the source, and we estimate the corresponding redshift using two methods: the redshifted masses and a galaxy catalog. Using the binary black hole (BBH) redshifted masses, we simultaneously infer the source mass distribution and H ( z ). The source mass distribution displays a peak around 34 M ⊙ , followed by a drop-off. Assuming this mass scale does not evolve with the redshift results in a H ( z ) measurement, yielding H 0 = 68 − 8 + 12 km s − 1 Mpc − 1 (68% credible interval) when combined with the H 0 measurement from GW170817 and its electromagnetic counterpart. This represents an improvement of 17% with respect to the H 0 estimate from GWTC–1. The second method associates each GW event with its probable host galaxy in the catalog GLADE+ , statistically marginalizing over the redshifts of each event’s potential hosts. Assuming a fixed BBH population, we estimate a value of H 0 = 68 − 6 + 8 km s − 1 Mpc − 1 with the galaxy catalog method, an improvement of 42% with respect to our GWTC–1 result and 20% with respect to recent H 0 studies using GWTC–2 events. However, we show that this result is strongly impacted by assumptions about the BBH source mass distribution; the only event which is not strongly impacted by such assumptions (and is thus informative about H 0 ) is the well-localized event GW190814. 

Abstract We present the results of a model-based search for continuous gravitational waves from the low-mass X-ray binary Scorpius X-1 using LIGO detector data from the third observing run of Advanced LIGO and Advanced Virgo. This is a semicoherent search that uses details of the signal model to coherently combine data separated by less than a specified coherence time, which can be adjusted to balance sensitivity with computing cost. The search covered a range of gravitational-wave frequencies from 25 to 1600 Hz, as well as ranges in orbital speed, frequency, and phase determined from observational constraints. No significant detection candidates were found, and upper limits were set as a function of frequency. The most stringent limits, between 100 and 200 Hz, correspond to an amplitude h 0 of about 10 −25 when marginalized isotropically over the unknown inclination angle of the neutron star’s rotation axis, or less than 4 × 10 −26 assuming the optimal orientation. The sensitivity of this search is now probing amplitudes predicted by models of torque balance equilibrium. For the usual conservative model assuming accretion at the surface of the neutron star, our isotropically marginalized upper limits are close to the predicted amplitude from about 70 to 100 Hz; the limits assuming that the neutron star spin is aligned with the most likely orbital angular momentum are below the conservative torque balance predictions from 40 to 200 Hz. Assuming a broader range of accretion models, our direct limits on gravitational-wave amplitude delve into the relevant parameter space over a wide range of frequencies, to 500 Hz or more.