Thanks :) @Eric Forgy: I hope that we can bring some of the comfort you have in the Web to native Julia and GPU computing ;) If and when that'll be achieved is an open question...
>I haven't tried GLVisualize - isn't there a problem with high-performance 3D in a stop-the-world GC'ed language like Julia? There definitely is. Luckily, in the scientific world throughput is more important than minor stutters, so this should give us some time to let the GC and visualization infrastructure grow up. Right now, GLVisualize is mostly pretty smooth and if it's not smooth, it should mainly be because of the event system. If 3D visualization in Julia works out to a point that people get serious about it, I'm sure we will figure out ways to make the GC less of an issue. Vulkan needs a lot of manual memory management anyways, so one might just expand on that and don't really put any pressure on the GC. It might also be possible to create low latency threads, which don't get interrupted by the GC. Am Samstag, 9. April 2016 19:32:53 UTC+2 schrieb Simon Danisch: > > Valentin <https://github.com/vchuravy> and I are proud to announce a > Julia wrapper for the Vulkan API <https://www.khronos.org/vulkan/>: > VulkanCore.jl <https://github.com/JuliaGPU/VulkanCore.jl> > > Vulkan can be called the successor of OpenGL, but it's a lot closer to the > hardware, which is why it's not a direct replacement of OpenGL. > > In short, the main differences to OpenGL are: > > - lower driver overhead > - better utilization of multi-core setups > - shader/kernel are consumed in form of a new intermediate format, > SPIR-V <https://www.khronos.org/registry/spir-v/specs/1.0/SPIRV.pdf>, > which can be targeted by any language (yes, especially Julia+LLVM) > - better low-level abstraction for GPU-CPU/GPU-GPU synchronization and > memory management > - GPGPU becomes more of a first class citizen > - supports a large variety of hardware and platforms (NVIDIA, AMD, > Intel, ARM, Android, Linux, Windows > <https://en.wikipedia.org/wiki/Vulkan_(API)>...) > > One of the more exciting use cases of Vulkan is running Julia kernels over > GPU-Arrays and then seamlessly visualizing the results. > Enabling this will be a lot of work. Please stay tuned for further posts > and watch the progress at Vulkan.jl > <https://github.com/JuliaGPU/Vulkan.jl>, the (not yet finished) higher > level abstraction over VulkanCore.jl. > > You can find some more information in a blog post > <http://randomfantasies.com/2016/02/why-im-betting-on-vulkan-and-julia/> > I recently wrote. > > Best, > Simon >
