What are the skills and competencies required for HPC cluster administrators and users?

For admins: - System Administration: Proficiency in Linux/Unix and cluster management tools like SLURM. - Networking and Storage: Knowledge of high-performance networking (Infiniband) and scalable storage systems. - Performance Tuning: Ability to troubleshoot and optimize computational workloads. For users: - Parallel Computing: Understanding of MPI, OpenMP, and GPU programming for scaling applications. - Job Scheduling: Familiarity with submitting and managing jobs using SLURM or similar schedulers. - Optimization: Skills in code profiling and performance optimization for efficient resource usage.

Cluster architecture design and execution in cluster computing is a complex process that involves integrating several technologies and taking many factors into account. The physical and logical configuration of nodes, which affects fault tolerance, scalability, and communication efficiency, is determined by the topology, which is crucial to all of this. Systems for resource management and task scheduling automate the distribution of resources, while middleware like MPI and OpenMP facilitate coordination and communication across nodes. Essentially, these elements are integrated by a well-designed cluster architecture to provide the best possible performance, scalability, and reliability for a variety of computing workloads.

While it isn't exactly a "protocol," software layers such as CUDA are also widely used in cluster computing, as an interface to graphical processing units (GPUs).

Familiarity with cluster management tools and software platforms such as Slurm, PBS Pro, Torque, Maui, and Kubernetes for job scheduling, resource allocation, and workload management in HPC environments.

?? HPC Cluster Administrators System Administration – Proficiency in Linux (RHEL, Ubuntu, CentOS), shell scripting, and system automation (Ansible, Puppet, Bash). Networking & Security – Knowledge of InfiniBand, Ethernet, RDMA, firewalls, and secure access (LDAP, Kerberos, SSH, VPNs). HPC Users (Researchers, Developers, Data Scientists) Programming & Parallelism – Strong skills in C, C++, Python, Fortran, and parallel computing frameworks (MPI, OpenMP, CUDA, HIP, SYCL). Job Scheduling & Workload Management – Experience with Slurm, PBS, and cloud HPC platforms (AWS, Azure, Google Cloud).

Tips from my article: "Fifteen quick tips for success with HPC..." 1: Do the HPC induction: Read the manual 2: Brush up on your Linux commands and BASH 3: Do not run your commands on a login node 4: Do not wait for the cluster load to decrease to submit jobs 5: Be aware of the file system 6: Take care with large file transfers 7: Be aware of any recharge model 8: Do not use Unicode characters in file paths 9: Understand the levels of parallelism required by your job 10: Identify potential bottlenecks in your job 11: Submit your job(s) to the correct queue(s) 12: Consider a package manager 13: Consider containerisation 14: Use a workflow language for your analysis pipeline 15: Use a Jupyter Notebook via an interactive session

Ability to optimize HPC cluster performance by tuning hardware configurations, optimizing software settings, and implementing performance-enhancing techniques such as parallelization, vectorization, and memory management. Proficiency in troubleshooting hardware and software issues, diagnosing performance bottlenecks, and debugging errors in HPC applications and workflows using tools such as GDB, DTrace, or Valgrind.