Tootfinder

#LinuxFoundation Launches #OpenSource Valkey Community
https://www.

“The adverse cognitive impact was worst with the original (ancestral) virus and the Alpha variant, compared with subsequent Delta and Omicron variants, and there was some protective effect of vaccination.” @…
Cognition and Memory after Covid-19 in a Large Community Sample | NEJM

I learned that one of the advantages of cloudcomputing is the more efficient use of resources. On a shared infrastructure you don't need the maximum amount of compute and memory all the time so you can share. In this blog they looked at how efficient kubernetes clusters worked. The outcomes are terrible. Massive overprovisioning of compute and memory.

Kubernetes Clusters Have Massive Overprovisioning Of Compute And Memory
In the ten years since Google released Kubernetes to the open source community, it has become the dominant platform for orchestrating and managing

This https://arxiv.org/abs/2312.13936 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

GVE-Leiden: Fast Leiden Algorithm for Community Detection in Shared Memory Setting
Community detection is the problem of identifying natural divisions in networks. Efficient parallel algorithms for identifying such divisions is critical in a number of applications, where the size of datasets have reached significant scales. This technical report presents an optimized parallel implementation of Leiden, a high quality community detection method, for shared memory multicore systems. On a server equipped with dual 16-core Intel Xeon Gold 6226R processors, our Leiden implementatio…

> trains are the crabs of transportation technology
I feel like I've seen this conversation with @… somewhere recently, or maybe it's just my memory of THE TERRAFORMERS
good insight @… ! Thanks!
🦀 🚆

This https://arxiv.org/abs/2312.08140 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

GVE-LPA: Fast Label Propagation Algorithm (LPA) for Community Detection in Shared Memory Setting
Community detection is the problem of identifying natural divisions in networks. Efficient parallel algorithms for this purpose are crucial in various applications, particularly as datasets grow to substantial scales. This technical report presents an optimized parallel implementation of the Label Propagation Algorithm (LPA), a high speed community detection method, for shared memory multicore systems. On a server equipped with dual 16-core Intel Xeon Gold 6226R processors, our LPA, which we te…

Linking Through Time: Memory-Enhanced Community Discovery in Temporal Networks
Giulio Virginio Clemente, Diego Garlaschelli
https://arxiv.org/abs/2402.10141

Linking Through Time: Memory-Enhanced Community Discovery in Temporal Networks
Temporal Networks, and more specifically, Markovian Temporal Networks, present a unique challenge regarding the community discovery task. The inherent dynamism of these systems requires an intricate understanding of memory effects and structural heterogeneity, which are often key drivers of network evolution. In this study, we address these aspects by introducing an innovative approach to community detection, centered around a novel modularity function. We focus on demonstrating the improvement…

This https://arxiv.org/abs/2312.04876 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

GVE-Louvain: Fast Louvain Algorithm for Community Detection in Shared Memory Setting
Community detection is the problem of identifying natural divisions in networks. Efficient parallel algorithms for identifying such divisions is critical in a number of applications, where the size of datasets have reached significant scales. This technical report presents one of the most efficient multicore implementations of the Louvain algorithm, a high quality community detection method. On a server equipped with dual 16-core Intel Xeon Gold 6226R processors, our Louvain, which we term as G…

This https://arxiv.org/abs/2312.04876 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

GVE-Louvain: Fast Louvain Algorithm for Community Detection in Shared Memory Setting
Community detection is the problem of identifying natural divisions in networks. Efficient parallel algorithms for identifying such divisions is critical in a number of applications, where the size of datasets have reached significant scales. This technical report presents one of the most efficient multicore implementations of the Louvain algorithm, a high quality community detection method. On a server equipped with dual 16-core Intel Xeon Gold 6226R processors, our Louvain, which we term as G…

This https://arxiv.org/abs/2312.13936 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

GVE-Leiden: Fast Leiden Algorithm for Community Detection in Shared Memory Setting
Community detection is the problem of identifying natural divisions in networks. Efficient parallel algorithms for identifying such divisions is critical in a number of applications, where the size of datasets have reached significant scales. This technical report presents an optimized parallel implementation of Leiden, a high quality community detection method, for shared memory multicore systems. On a server equipped with dual 16-core Intel Xeon Gold 6226R processors, our Leiden implementatio…

This https://arxiv.org/abs/2312.13936 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

GVE-Leiden: Fast Leiden Algorithm for Community Detection in Shared Memory Setting
Community detection is the problem of identifying natural divisions in networks. Efficient parallel algorithms for identifying such divisions is critical in a number of applications, where the size of datasets have reached significant scales. This technical report presents an optimized parallel implementation of Leiden, a high quality community detection method, for shared memory multicore systems. On a server equipped with dual 16-core Intel Xeon Gold 6226R processors, our Leiden implementatio…