Inside a PC, one stream of light flows into a large graphics card and another into the integrated processor at the same time

Rust ONNX Runtime for AMD GPUs

Software & SaaS
Software & SaaS

Rust ONNX Runtime for AMD GPUs

Windows driver and runtime limitations kept AMD GPUs from running a broad range of models locally. RemSoft.Dev developed custom Rust software to run ONNX models on AMD GPUs through WSL/ROCm, overcoming those limitations. For a local RAG workload, the engine parallelizes execution across a powerful discrete GPU and an integrated GPU: indexing stays on the primary GPU while a second RAG instance serves search on the integrated GPU. Search remains available during indexing, hardware utilization improves, and the platform can run a broad range of Hugging Face ONNX models instead of being limited to GGUF/Llama formats. The same Rust layer powers local model execution in Dew Flow, our multi-agent development orchestrator.

RustGPUONNXLocal AI

Key Challenges

Client: RemSoft.Dev platform, used on client projects

Hardware: AMD discrete + integrated GPU

Runtime: Rust, ONNX, WSL/ROCm

Workload: Local RAG indexing and search

The project faced several key challenges:

  • Windows limitations: Windows drivers and runtimes blocked AMD GPUs from running many models - the engine runs them through WSL and ROCm instead.
  • Search blocked by indexing: A single GPU busy with indexing cannot serve search. Splitting the work across two GPUs keeps both running.
  • Format lock-in: Being limited to GGUF/Llama formats rules out most Hugging Face models - ONNX opens the broad catalog.

Results

  • Search available during indexing
  • Better hardware utilization across two GPUs
  • Broad range of Hugging Face ONNX models
  • No longer limited to GGUF/Llama formats

2 GPUs

discrete for indexing, integrated for search - in parallel.

Always on

search stays available while indexing runs.

ONNX

a broad Hugging Face model catalog instead of GGUF only.

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