bookmarks - animeshtrivedi/notes GitHub Wiki
- 20th ECMWF workshop on high performance computing in meteorology https://ecmwfevents.com/i/20th-ecmwf-workshop-on-high-performance-computing-in-meteorology/public/agenda
- https://hackmd.io/@mono/BJj_uNU-P Study Notes for NVMe
- Graph Generators: State of the Art and Open Challenges, ACM CACM, https://dl.acm.org/doi/abs/10.1145/3379445
- Programming Workbench Compressed Sparse Row Format for Representing Graphs https://www.usenix.org/system/files/login/articles/login_winter20_16_kelly.pdf
- Graph Storage: How good is CSR really? https://db.in.tum.de/teaching/ws1718/seminarHauptspeicherdbs/paper/valiyev.pdf
- https://graphscope.io/blog/tech/2023/08/29/GraphAr-A-Standard-Data-File-Format-for-Graph-Data-Storage-and-Retrieval
- An analysis of the graph processing landscape https://arxiv.org/pdf/1911.11624
Numerical sampling
- NumericalStats: How to randomly sample your empirical arbitrary distribution https://alpynepyano.github.io/healthyNumerics/posts/sampling_arbitrary_distributions_with_python.html
- https://www.fast.ai/posts/2019-01-13-swift-random.html C++11, random distributions, and Swift
- https://en.wikipedia.org/wiki/Rejection_sampling
- https://en.wikipedia.org/wiki/Ziggurat_algorithm
- https://ch.mathworks.com/matlabcentral/fileexchange/7976-random-number-from-empirical-distribution
- https://en.wikipedia.org/wiki/Empirical_distribution_function