{"id":20880237,"url":"https://github.com/betarixm/csed490c","last_synced_at":"2026-04-19T03:02:03.410Z","repository":{"id":215069440,"uuid":"698104536","full_name":"betarixm/CSED490C","owner":"betarixm","description":"POSTECH: Heterogeneous Parallel Computing (Fall 2023)","archived":false,"fork":false,"pushed_at":"2024-01-02T07:48:19.000Z","size":1334,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-19T09:44:26.682Z","etag":null,"topics":["cuda","gpu","parallel-computing","postech"],"latest_commit_sha":null,"homepage":"","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/betarixm.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2023-09-29T07:01:53.000Z","updated_at":"2024-01-02T08:32:42.000Z","dependencies_parsed_at":"2024-01-02T10:58:23.425Z","dependency_job_id":"1ea568e4-b26c-421d-bf74-036d738e25b3","html_url":"https://github.com/betarixm/CSED490C","commit_stats":null,"previous_names":["betarixm/csed490c"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/betarixm%2FCSED490C","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/betarixm%2FCSED490C/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/betarixm%2FCSED490C/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/betarixm%2FCSED490C/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/betarixm","download_url":"https://codeload.github.com/betarixm/CSED490C/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243258496,"owners_count":20262297,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cuda","gpu","parallel-computing","postech"],"created_at":"2024-11-18T07:19:34.229Z","updated_at":"2025-10-17T11:31:17.414Z","avatar_url":"https://github.com/betarixm.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Heterogeneous Parallel Computing\n\n[![CSED490C@POSTECH](https://img.shields.io/badge/CSED490C-POSTECH-c80150)](https://www.postech.ac.kr/eng)\n[![CSED490C@POSTECH](https://img.shields.io/badge/Fall-2023-775E64)](https://www.postech.ac.kr/eng)\n\nHeterogeneous parallel systems with a host CPU and various devices provide high performance and energy efficiency and are widely adopted from supercomputers to edge devices. In this course, you will learn common architectures and parallel algorithm patterns for heterogeneous systems, high-level programming interfaces for HPC and AI applications (OpenCL/OpenMP, TensorFlow), and performance optimization techniques, etc. and work on programming projects.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbetarixm%2Fcsed490c","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbetarixm%2Fcsed490c","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbetarixm%2Fcsed490c/lists"}