Introduction

FutureSDR is a software-defined radio (SDR) runtime written in Rust with a focus on portability, performance, and developer ergonomics.

Main Features

• Platform support: FutureSDR runs on Linux, Windows, macOS, Android, and on the web. Support for both native and browser targets allows you to reuse the same signal-processing code across desktop, embedded, and WebAssembly deployments.
• Accelerators: FutureSDR integrates with accelerators through custom buffers that provide direct access to accelerator memory (e.g., DMA buffers, GPU staging buffers, machine-learning tensors). Developers can implement their own buffers or reuse existing ones for Xilinx Zynq DMA, Vulkan GPU, and Burn, a Rust machine-learning framework.
• Custom Schedulers: FutureSDR uses an async runtime that schedules data-processing workloads as user-space tasks. This architecture lets you plug in different scheduling strategies to match your latency and throughput goals.

Core Concepts

While FutureSDR’s implementation differs from other SDR frameworks, the core abstractions remain familiar. It supports Blocks that implement stream-based or message-based data processing. These blocks can be combined into a Flowgraph and launched on a Runtime that is driven by a Scheduler.

Documentation Structure

User Documentation explains how to:

• Use an existing FutureSDR application (an example or a thrid party implementation).
• Interface a FutureSDR application through the built-in or a custom web interface.
• Interface a FutureSDR application through the REST API (e.g., Curl or a custom Python script).

Application Development explains how to;

• Create FutureSDR applications using existing blocks.
• Interact with running flowgraphs through Rust code.
• Integrate FutureSDR in a broader application, potentially with custom GUIs.

SDR Development explains how to:

• Implement custom blocks for specific technologies or custom integrations.
• Extend FutureSDR with custom buffers or custom schedulers.