30 open-source projects similar to schedmd/slurm, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Slurm alternative.
Polyaxon is a Kubernetes-native machine learning orchestration platform and MLOps pipeline orchestrator. It serves as a control plane for managing distributed deep learning workloads, automated machine learning pipelines, and experiment tracking. The platform distinguishes itself through specialized services for distributed training management, including MPI-based coordination for PyTorch and TensorFlow. It provides an automated hyperparameter optimization service utilizing Bayesian, random, and grid search algorithms, alongside managed interactive AI workspaces for launching Jupyter notebook
Azure Docs is the official technical documentation repository for Microsoft Azure, the cloud computing platform. It provides comprehensive guidance on the full spectrum of Azure services, covering everything from core infrastructure components like virtual machines, Kubernetes clusters, and serverless computing to platform services for AI, machine learning, data analytics, and storage. The documentation details how to provision, manage, and govern cloud resources at scale, including policy enforcement, identity management, and cost optimization. The documentation distinguishes Azure through i
This project provides a comprehensive technical guide and framework for engineering large-scale machine learning systems. It covers the full lifecycle of model development, focusing on the infrastructure and computational principles required to build, train, and serve generative AI models across distributed GPU clusters. The repository distinguishes itself by offering deep-dive tutorials and implementation strategies for complex system challenges. It emphasizes high-performance architectural primitives, such as collective communication orchestration, distributed tensor sharding, and static gr
Inngest is a durable execution framework and event-driven automation engine designed to orchestrate background workflows. It enables developers to build resilient, stateful processes by memoizing function steps, ensuring that long-running tasks can automatically resume from the last successful operation after failures, timeouts, or infrastructure restarts. The platform distinguishes itself through its event-driven architecture, which uses a schema-validated bus to trigger functions and coordinate complex, multi-step logic. It employs an onion-model middleware approach for cross-cutting concer
Dask is a parallel computing framework and distributed task scheduler designed to scale Python data science workflows from single machines to large clusters. It functions as a cluster resource manager that orchestrates computational logic by representing tasks and their dependencies as directed acyclic graphs. This architecture allows the system to automate the distribution of workloads across available hardware while managing complex execution requirements. The project distinguishes itself through a lazy evaluation engine that defers data operations until they are explicitly requested, enabl
Official MAAS repository. Bugs are tracked on Launchpad: https://bugs.launchpad.net/maas
cuDF is a GPU-accelerated dataframe library and data processing engine designed for manipulating and analyzing large tabular datasets. It provides a high-level API for executing filtering, joining, and aggregating operations directly on GPU hardware. The project integrates the Apache Arrow memory format to enable zero-copy data transfers and includes a just-in-time compiler for executing custom user-defined functions on the GPU. The library features specialized acceleration for existing workflows by redirecting standard Pandas dataframe calls and Polars query plans to a GPU backend. It also p
LocalStack is an infrastructure development environment that provides a local simulation of cloud services. By leveraging container-orchestrated service lifecycles, it allows developers to build, test, and debug cloud-native applications on their local machines without requiring remote connectivity or incurring cloud provider costs. The platform distinguishes itself through sophisticated traffic redirection and request routing, which intercept cloud service calls at the network layer and redirect them to local handlers. This enables seamless integration with existing development workflows, al
NVIDIA Docker is a container runtime wrapper that enables the use of host-level graphics processing units within isolated container environments. It functions as a containerized GPU orchestrator, mapping physical hardware resources into virtualized environments to support high-performance computing and machine learning workloads. The project provides a toolkit that facilitates integration between containerized applications and host-level graphics hardware. By utilizing a pre-start hook to intercept container creation, the runtime injects necessary device drivers and libraries into the isolate
JupyterHub is a multi-user platform for hosting and managing isolated Jupyter notebook server instances on a single system or cluster. It serves as a notebook server orchestrator that spawns and monitors individual computing environments on demand. The system uses a plugin-based spawner interface to launch these environments across diverse infrastructure, including local processes, containers, or cloud clusters. It integrates with external identity providers and supports pluggable authentication to verify user identities and secure access. The framework includes centralized administration to
noVNC is an HTML5 remote desktop viewer and VNC web client that allows users to access and control remote desktops, virtual machines, and containers through a web browser. It functions as a remote desktop management tool that integrates the VNC protocol to enable remote server administration without the need for a dedicated client application. The project includes a VNC WebSocket proxy that translates binary VNC network traffic into WebSockets to bypass browser restrictions on direct TCP connections. This proxy service supports bridging connections to multiple remote servers by listening on v
Ansible is an agentless infrastructure automation engine designed to manage remote servers and network devices. It functions as a cross-platform orchestration tool that coordinates system updates, software installations, and service configurations from a centralized management workstation. By utilizing a declarative approach, it allows users to define desired system states through human-readable configuration files, ensuring consistency across distributed environments. The platform operates by establishing secure shell connections to target nodes, eliminating the need for persistent agent sof
Portainer is a unified infrastructure management platform that provides a centralized control plane for deploying, monitoring, and managing containerized applications. It functions as an orchestration-abstraction layer, translating user actions into platform-specific API calls to maintain consistency across diverse container runtimes and cluster technologies. By organizing users, teams, and resources into a single interface, it enables granular role-based access control and lifecycle management for containerized services and stacks. The platform distinguishes itself through its support for di
Triton Inference Server is a high-performance AI model inference server and multi-framework model runtime designed for deploying machine learning models across cloud, data center, and embedded edge infrastructure. It serves as an execution engine that allows for the concurrent running of models from various frameworks to optimize hardware utilization. The project features a dynamic batching inference engine that groups individual requests into larger batches to increase total processing throughput. It also provides a model ensemble pipeline, which enables the chaining of multiple models toget
Collect logs for docker containers
Kubeflow is a Kubernetes machine learning platform and containerized toolkit designed to orchestrate the entire machine learning lifecycle. It functions as an MLOps workflow orchestrator and infrastructure layer for building, training, and deploying models within containerized environments. The project provides specialized infrastructure for scaling compute resources and managing GPU workloads for large-scale distributed training. It automates the transition of models from experimental development to production through workflow orchestration and model deployment services. The platform covers
Traefik is a cloud-native load balancer and dynamic reverse proxy designed for microservices traffic routing. It automatically discovers services and generates network routes by listening to infrastructure changes in orchestrators and service registries. The project distinguishes itself through auto-configuring service routing, which eliminates manual configuration by updating routing rules in real time as infrastructure scales. It also provides automated SSL certificate management, utilizing ACME-based automation to request and renew certificates from remote authorities. Additional capabili
pyinfra is an agentless infrastructure automation framework that turns declarative Python code into idempotent shell commands to manage servers, containers, and local machines over SSH without requiring any pre-installed software on target hosts. It operates by comparing the desired state of a system against its current state, using a dry-run simulation mode to preview changes and a fact-based conditional execution engine to gather host attributes at runtime and control which operations run. The tool compiles Python operations into optimized shell commands and executes them in parallel across
docker-py is a Python library and SDK that serves as a programmatic client for the Docker Engine API. It provides a programmatic interface for controlling containers, images, and clusters, allowing for the automation of containerized applications and engine resources. The library enables remote Docker administration through various transport methods, including Unix domain sockets, TCP ports, and encrypted SSH tunnels. It handles real-time data links by using WebSockets to stream input and output from active containers. The project covers container lifecycle control, image management for buil
Graylog2-server is an open-source centralized log management system and aggregator. It functions as a log analysis platform designed to collect, index, and analyze log data from multiple sources within a centralized searchable index. The system provides capabilities for enterprise log aggregation and infrastructure monitoring. It enables the gathering of logs from various servers and applications to facilitate log data analysis and root cause troubleshooting across a network. The platform utilizes a distributed indexing pipeline and message-queue based ingestion to handle log streams. It inc
A simple yet powerful tool to turn traditional container/OS images into unprivileged sandboxes.
Luigi is a Python framework designed for building and managing complex batch data pipelines. It functions as a workflow orchestration engine that organizes tasks into directed acyclic graphs, ensuring that jobs execute in the correct logical order based on their dependencies. By utilizing a centralized scheduler, the system coordinates task execution across distributed environments, tracks global workflow state, and prevents redundant processing by verifying the existence of output targets before triggering any work. The project distinguishes itself through a robust state-tracking mechanism t
This project is a distributed computing platform designed to orchestrate containerized workloads across heterogeneous hardware clusters. It functions as a centralized control plane that manages resource allocation, scheduling, and execution environments, enabling organizations to share high-performance computing infrastructure securely among multiple users and projects. The platform distinguishes itself through advanced hardware virtualization and multi-tenant management capabilities. It supports the partitioning of physical graphics processing units into fractional slices, allowing multiple
This project is a technical curriculum and set of educational resources focused on parallel programming, high-performance computing, and systems programming. It provides a structured course covering the implementation of parallel algorithms and multithreading techniques for processing large datasets. The project includes a systems programming guide for modern language features, a framework for lock-free concurrency patterns, and a manual for optimizing CPU and GPU performance through assembly analysis and cache management. The material covers hardware performance tuning, the implementation o
This project is a parallel simulation engine and molecular dynamics simulator designed to model the physical movements of atoms and molecules. It functions as an interatomic potential framework for calculating forces between particles and a materials analysis tool for computing thermodynamic, structural, and transport properties of solids and fluids. The engine is distinguished by its high-performance computing capabilities, utilizing spatial-domain decomposition and message-passing interface communication to distribute workloads across processors. It supports multi-backend GPU acceleration v
Accelerate is a framework for high-performance array computing that provides a domain-specific language for expressing complex mathematical and parallel computations. By utilizing a declarative programming interface, it allows users to define high-level array transformations that are automatically translated into optimized machine code for diverse hardware architectures. The system distinguishes itself through a modular architecture that decouples high-level array operations from hardware-specific instructions. It employs just-in-time compilation and kernel fusion to transform programs into e
Spack is a source-based build system and package manager designed for high-performance computing. It serves as a multi-version software manager and a logic-based dependency solver that handles complex software stacks across various platforms and hardware architectures. The project distinguishes itself by managing multiple compilers and toolchains to target specific hardware. It allows the coexistence of multiple versions and configurations of the same software package on a single system by utilizing prefix-based isolation and unprivileged deployment. The system provides comprehensive capabil
ISPC is a vectorizing compiler and SIMD parallel programming language that implements a single program multiple data model. It serves as a toolchain for translating C-based code with parallel extensions into optimized machine code for various CPU and GPU architectures using an LLVM backend. The compiler is designed for cross-platform SIMD toolchain support, generating specialized instruction sets for x86 SSE/AVX, ARM NEON, and Intel GPU from a single source. It features a runtime dispatch mechanism that selects the most efficient hardware-specific implementation for the current system during
Parallel is a Ruby library and multi-process execution framework designed to accelerate CPU-intensive operations. It functions as a parallel job orchestrator and concurrent task runner that enables the execution of code across multiple processes or threads. The project distinguishes itself through secure inter-process communication, utilizing signed data serialization to prevent the injection of forged payloads between parent and child processes. It further differentiates its worker management by assigning unique identifiers to individual processes to prevent collisions when accessing shared