Glossary#
This glossary provides definitions for terms and abbreviations you may encounter when using our HPC cluster.
- Backfilling#
A scheduling technique that allows smaller jobs to be scheduled ahead of larger jobs, as long as they don’t impact the completion of larger high-priority jobs.
- Cluster#
A group of computers connected in a way that allows them to function as a single system.
- Cluster Manager#
A software system responsible for monitoring and managing the health, status, and communication among nodes in a cluster.
- Compute Node#
A component within a cluster that performs the actual computational tasks. It typically consists of multiple processors, memory, and storage resources, where the primary computation and data processing occur.
- Concurrency#
The ability of the system to handle multiple tasks or jobs simultaneously, without waiting for each task to complete before starting another.
- Container#
A lightweight, stand-alone, and executable package that includes everything needed to run a piece of software, including the code, runtime, system tools, libraries, and settings. Containers provide consistency and portability across different computing environments.
- Core#
A processor within a CPU. Each core can execute its tasks.
- Central Processing Unit (CPU)#
The primary component of a computer that performs most processing inside the computer. CPUs can have multiple cores.
A scheduling policy that ensures all users receive a fair share of cluster resources over time, regardless of job size or priority.
- Graphics Processing Unit (GPU)#
A specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device.
- GPU Acceleration#
The use of GPUs to offload computation-intensive tasks from the CPU, leading to faster processing of tasks like simulations and data analysis.
- Home Directory#
A user’s directory in the cluster where personal files, application settings, and other user-specific data are stored.
- High-Performance Computing (HPC)#
The use of parallel processing for running advanced application programs efficiently, reliably, and quickly. It’s often used for scientific research, big data analysis, and modeling complex systems.
- InfiniBand (IB)#
A high-speed networking technology commonly used in HPC clusters. It provides high bandwidth and low latency communication between nodes in the cluster, facilitating fast data transfer for parallel processing.
- Job#
A set of computations a user submits to the HPC cluster for execution.
- Job Dependency#
The condition where one job relies on the successful completion of another job before it can start, ensuring proper sequencing of tasks.
- Job Priority#
Refers to the relative importance or urgency assigned to a specific computational task or job within a High-Performance Computing (HPC) cluster’s scheduling system. Job priority determines the order in which jobs are executed and the allocation of computing resources.
In an HPC environment, different jobs may have varying degrees of importance or resource requirements. Job priority allows the cluster’s scheduler to make decisions on which job to execute next, considering factors such as:
User-defined Priority: Users can often assign priority values to their jobs, indicating the relative importance of their tasks. Higher priority values typically result in faster job execution.
Resource Requirements: Jobs with greater resource demands, such as more CPUs, memory, or GPUs, may receive higher priority, ensuring they receive the necessary resources for efficient execution.
Walltime Limit: Jobs with shorter estimated execution times may be assigned higher priority, as they are more likely to finish quickly and free up resources for other pending jobs.
By adjusting job priorities, users and administrators can optimize resource allocation, meet project deadlines, and promptly process critical tasks within the HPC cluster. Job priority management is an essential aspect of efficient cluster operation.
- Job Script#
A file that contains a series of commands that the HPC cluster will execute.
- Login Node#
A gateway or access point to an HPC cluster. Users connect to the login node to submit jobs, manage files, and interact with the cluster. However, it’s meant for something other than resource-intensive computations.
- Module#
In the context of HPC, a module is a bundle of software that can be loaded or unloaded in the user’s environment.
- Message Passing Interface (MPI)#
A standardized and portable message-passing system used to enable communication between nodes in a parallel computing environment.
- Node#
A single machine within a cluster. A node can have multiple processors and its memory and storage.
- Node Allocation#
The process of reserving a set of nodes for a specific job, ensuring that the required resources are available for successful execution.
- Open OnDemand (OOD)#
A web-based interface for accessing and managing HPC resources. It provides users a user-friendly way to submit jobs, manage files, and utilize cluster resources through a web browser.
- Overcommitment#
Allowing more resources to be allocated to jobs than physically available, relying on intelligent scheduling and efficient resource management.
- Package Manager#
A collection of software tools that automates the process of installing, upgrading, configuring, and removing computer programs for a computer in a consistent manner.
- Parallel Computing#
A type of computation in which multiple calculations or processes are carried out simultaneously to solve a problem faster.
- Partition#
A division of the cluster resources. Each partition can have different configurations, such as different types of nodes and different access policies.
- Quota#
A quota limits the storage or computing resources allocated to a user or a project within an HPC cluster. Quotas help manage resource usage and prevent resource exhaustion.
- Queue#
A waiting line for jobs ready to be executed but waiting for resources to become available.
- Resource Reservation#
The process of specifying resources required for a job in advance to ensure availability and prevent resource conflicts.
- Scheduling Policy#
A set of rules and algorithms used by the scheduler to determine the order in which jobs are executed based on their priority, resource requirements, and other factors.
- Scratch Space#
Temporary storage that allows users to store intermediate data during job execution. Data in scratch space is not preserved between jobs.
- Storage Cluster#
A set of networked storage devices used to provide centralized and scalable storage solutions for the HPC environment.
- Scheduler#
A program that manages the cluster’s resources and allocates them to jobs based on priority, requested resources, and fair use policies.
- Singularity#
A containerization platform commonly used in HPC environments. It allows users to create and run containers focusing on security and compatibility, making it suitable for running scientific applications.
- Slurm#
An open-source, fault-tolerant, and highly scalable cluster management and job scheduling system for large and small HPC clusters.
- Task#
A unit of work within a job that can be executed independently. A job can consist of multiple tasks.
- VPN#
A technology that creates a secure and encrypted connection over a public network, such as the Internet. It often provides remote access to HPC clusters, ensuring data privacy and security during remote cluster interactions.
This glossary is not exhaustive. If you come across a term not listed here, please check the specific section of the documentation or ask in our User Community and Forums.