remarcm

Remarcm is a modular, open-source framework for orchestrating distributed computations across heterogeneous clusters. It provides abstractions for remote tasks, data movement, and memory management, enabling developers to define computation graphs that span multiple machines and memory domains.

The architecture of remarcm centers on a lightweight core scheduler, a remote memory layer that maps data locations across nodes, and runtime adapters that plug into various execution engines (for example, container runtimes, MPI, or cloud function environments). The design emphasizes data locality, fault tolerance, and observability, with support for asynchronous execution, retries, and checkpointing.

Remarcm originated in open-source developer communities seeking to streamline hybrid-cloud workloads and multi-node experiments. It is maintained as a community-driven project with regular releases, comprehensive documentation, and optional commercial support channels in some ecosystems.

Features:

- Distributed task scheduling and graph execution

- Remote memory abstraction and data transfer primitives

- Adapter-based backends for different runtimes

- Fault tolerance, retries, and checkpointing

- Observability through metrics and tracing

- Cross-language bindings and SDKs

Usage:

Developers integrate remarcm by defining tasks and data dependencies in the provided API, then launching the graph on a cluster. Remarcm handles scheduling, data movement, and failure recovery, allowing applications to scale across nodes without bespoke orchestration code.

See also:

Distributed computing, Cloud orchestration, Parallel computing frameworks.