Getting Started with RTXMU SDK
Reducing Memory Consumption with an Open Source Solution
Download RTXMU SDK
System Requirements
Operating System | Windows 10 SDK v1809 (17763), or higher |
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Supported GPUs | NVIDIA GeForce and Quadro products with Pascal and newer generation GPUs |
Supported Drivers | Latest NVIDIA Display Driver |
Development Environment | CMake 3.15, or higher Visual Studio 2017 or 2019 |
RTXMU SDK
RTXMU combines both compaction and suballocation techniques to optimize and reduce memory consumption of acceleration structures for any DXR or Vulkan Ray Tracing application.
Access GitHubRelease Notes
RTXMU SDK v1.1
- Fixed issue of missing functions in the Vulkan dispatch table.
- Validate initial build memory sizes prior to rebuilding the same acceleration structure.
- Always deallocate scratch memory in garbage collection and reallocate if needed for rebuilding an acceleration structure.
- Supports multiple devices in the case of multi gpu, etc.
FAQ
A: RTXMU (RTX Memory Utility) combines both compaction and suballocation techniques to optimize and reduce memory consumption of acceleration structures for any DXR or Vulkan Ray Tracing application.
A: RTXMU provides a simple interface that abstracts away the low level details of compaction and suballocation.
A: Works for both DXR 1.0, 1.1 along with Vulkan Ray Tracing. RTXMU SDK does not shoot any rays, it only manages the acceleration structures.
A: NVIDIA: GTX 1000, RTX 2000 and RTX 3000 series GPUs. AMD: Radeon RX 6000 series GPUs.
A: Compaction reduces the size of acceleration structures and suballocation allows smaller memory alignment requirements when packing multiple acceleration structures into a single allocation.
A: The open source initiative of RTXMU allows console developers to implement their own version. NVIDIA only provides a Vulkan and DX RT sample implementation.
A: Disabled compaction is the most likely culprit. All acceleration structures builds must have the Allow Compaction flag for RTXMU to prepare compaction workloads.
Resources
RTXMU Technical Blog: Reducing Acceleration Structure Memory with NVIDIA RTXMU