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1. Head in the clouds

   https://doi.org/10.1016/S0262-4079(23)00580-8  

   Ponsford, Matthew (April 2023, New Scientist)
2. Sequential Point Clouds: A Survey

   https://doi.org/10.1109/TPAMI.2024.3365970  

   Wang, Haiyan; Tian, Yingli (August 2024, IEEE Transactions on Pattern Analysis and Machine Intelligence)
3. Tracing Function Dependencies across Clouds

   https://doi.org/10.1109/CLOUD.2018.00039  

   Lin, Wei-Tsung; Krintz, Chandra; Wolski, Rich (July 2018, IEEE International Conference on Cloud Computing (CLOUD))

   In this paper, we present Lowgo, a crosscloud tracing tool for capturing causal relationships in serverless applications. To do so, Lowgo records dependencies between functions, through cloud services, and across regions to facilitate debugging and reasoning about highly concurrent, multi-cloud applications. We empirically evaluate Lowgo using microbenchmarks and multi-function and multi-cloud applications. We find that Lowgo is able to capture causal dependencies with overhead that ranges from 2-12%, which is less than half that of the best-performing, cloud-specific approach. 

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4. Clusters, clouds, and correlations: relating young clusters to giant molecular clouds in M33 and M31

   https://doi.org/10.1093/mnras/stad1430  

   Peltonen, Joshua; Rosolowsky, Erik; Johnson, L. Clifton; Seth, Anil C.; Dalcanton, Julianne; Bell, Eric F.; Braine, Jonathan; Koch, Eric W.; Lazzarini, Margaret; Leroy, Adam K.; et al (May 2023, Monthly Notices of the Royal Astronomical Society)

   ABSTRACT We use young clusters and giant molecular clouds (GMCs) in the galaxies M33 and M31 to constrain temporal and spatial scales in the star formation process. In M33, we compare the Panchromatic Hubble Andromeda Treasury: Triangulum Extended Region (PHATTER) catalogue of 1214 clusters with ages measured via colour–magnitude diagram (CMD) fitting to 444 GMCs identified from a new 35 pc resolution Atacama Large Millimeter/submillimeter Array (ALMA) 12CO(2–1) survey. In M31, we compare the Panchromatic Hubble Andromeda Treasury (PHAT) catalogue of 1249 clusters to 251 GMCs measured from a Combined Array for Research in Millimeter-wave Astronomy (CARMA) 12CO(1–0) survey with 20 pc resolution. Through two-point correlation analysis, we find that young clusters have a high probability of being near other young clusters, but correlation between GMCs is suppressed by the cloud identification algorithm. By comparing the positions, we find that younger clusters are closer to GMCs than older clusters. Through cross-correlation analysis of the M33 cluster data, we find that clusters are statistically associated when they are ≤10 Myr old. Utilizing the high precision ages of the clusters, we find that clusters older than ≈18 Myr are uncorrelated with the molecular interstellar medium (ISM). Using the spatial coincidence of the youngest clusters and GMCs in M33, we estimate that clusters spend ≈4–6 Myr inside their parent GMC. Through similar analysis, we find that the GMCs in M33 have a total lifetime of ≈11–15 Myr. We also develop a drift model and show that the above correlations can be explained if the clusters in M33 have a 5–10 km s−1 velocity dispersion relative to the molecular ISM. 

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5. Memtrade: Marketplace for Disaggregated Memory Clouds

   https://doi.org/10.1145/3589985  

   Maruf, Hasan Al; Zhong, Yuhong; Wang, Hongyi; Chowdhury, Mosharaf; Cidon, Asaf; Waldspurger, Carl (May 2023, Proceedings of the ACM on Measurement and Analysis of Computing Systems)

   We present Memtrade, the first practical marketplace for disaggregated memory clouds. Clouds introduce a set of unique challenges for resource disaggregation across different tenants, including resource harvesting, isolation, and matching. Memtrade allows producer virtual machines (VMs) to lease both their unallocated memory and allocated-but-idle application memory to remote consumer VMs for a limited period of time. Memtrade does not require any modifications to host-level system software or support from the cloud provider. It harvests producer memory using an application-aware control loop to form a distributed transient remote memory pool with minimal performance impact; it employs a broker to match producers with consumers while satisfying performance constraints; and it exposes the matched memory to consumers through different abstractions. As a proof of concept, we propose two such memory access interfaces for Memtrade consumers -- a transient KV cache for specified applications and a swap interface that is application-transparent. Our evaluation using real-world cluster traces shows that Memtrade provides significant performance benefit for consumers (improving average read latency up to 2.8X) while preserving confidentiality and integrity, with little impact on producer applications (degrading performance by less than 2.1%). 

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