Partitioning

#include <bits/stdc++.h>using namespace std;  struct Info {    int sum;    vector<int> indices;};  static bool cmp(Info& p1, Info& p2){    return p1.sum < p2.sum;}  void generate(vector<int>& arr, int curr, int n, int sum,              vector<vector<Info> >& store,              vector<int> build){    if (curr == n) {        int sz = build.size();        store.push_back({ sum, build });        return;    }    build.push_back(curr);    generate(arr, curr + 1, n, sum +…

Maximize GPU utilization and reduce infrastructure costs.Photo by Growtika on UnsplashTo minimize infrastructure expenses, it’s crucial to use GPU accelerators in the most efficient way. One method to achieve this is by dividing the GPU into smaller partitions, called slices, so that containers can request only the strictly necessary resources. Some workloads may only require a minimal amount of the GPU’s compute and memory, so having the ability in Kubernetes to divide a single GPU into multiple slices, which can be…

How can we quickly find overlapping trajectories?Photo by Jens Lelie on UnsplashWhile traveling through space, an object describes a trajectory. We can think about a trajectory as a function of time that outputs positions in space. Conceptually, trajectories are continuous functions, although we pragmatically use their discrete versions. A discrete trajectory is a time-ordered collection of points in space where we implicitly assume a linear interpolation between each point. This representation makes storing discrete…

Photo by D koi on UnsplashGraph partitioning has been a long-lasting problem and has a wide range of applications. This post shares the methodology for graph partitioning with both theoretical explanations and practical implementations of some popular graph partitioning algorithms with python codes.Clarification“Clustering” can be confusing under different contexts. In this article, clustering means node clustering, i.e. partitioning the graphs into clusters (or communities). We use graph partitioning, (node) clustering,…