The output can be many thousands of individual datasets. So What Are We Actually Doing?ĭepending on the simulation domain we can be dealing with a variety of topologies from uniform voxel domains to tetrahedral meshes to octree structures and the resulting datasets are often timeseries with hundreds of discrete timesteps over a number of physics types.

Given the results of the compute are targeted at interactive visualization we wanted a solution that could be enabled for graphics as well so Vulkan was the only viable choice. While our various solvers use a variety of technologies to perform their computations on both the CPU and GPU we decided to unify on a portable, modern explicit GPU API for our post processing system. We had faced limitations on the capabilities of OpenGL on some platforms and an explicit API gives us much more control over how the GPU operates. Vulkan has brought us both flexible compute and graphics along with a vendor-agnostic implementation in a way no other GPU API has before. Clients need to be able to inspect the data by generating visualizations on-the-fly which requires an architecture that can handle transient compute processes that don’t simply reserve cloud computing capacity for the duration of a user session. This is something that has become more of a pressing issue as the simulation capabilities of Autodesk Fusion 360 have expanded.Īt Autodesk we rely heavily on cloud computing to make all of this happen and from the perspective of simulation post-processing - being the processing of the data that is the result of the simulation - we have been leveraging GPU resources in the cloud to generate visualizations of simulation data. When you have datasets this large it can be difficult to distill this down into something that you can derive valuable insights from and keeping these enormous datasets in the cloud allows us to use scalable cloud resources to process the data.

Even with modern GPU acceleration and large amounts of memory the resolution of the domain required to accurately simulate even a subset of real-world physics can result in compute times that run into the days or even weeks and datasets that are many tens of gigabytes in size. In the world of simulation we are accustomed to dealing with both extremely large datasets and very long compute times.

Fusion 360 gpu rendering