BENDA PARALLEL LANGUAGEWith Bend you can write parallel code for multi-core CPUs/GPUs without being a C/CUDA expert with 10 years of experience. It feels just like Python! No need to deal with the complexity of concurrent programming: locks, mutexes, atomics... any work that can be done in parallel will be done in parallel. HVMA PARALLEL RUNTIMEIn 1997, Yves Lafont devised a concurrent computation
［GDC 2024］CPUを使わずにGPUが自発的に描画するパイプライン「Work Graph」がDirectX 12に正式採用 ライター：西川善司 セッションタイトルを訳すなら，「ようこそ，未来のGPUプログラミングモデル『GPU Work Graph』へ」 米国時間2024年3月18日に行われたGDC 2024の技術セッション「Advanced Graphics Summit: GPU Work Graphs: Welcome to the Future of GPU Programming」において，AMDとMicrosoftは共同で，DirectX 12の新機能「Work Graph」を発表した（関連リンク）。本稿では，Work Graphとは何で，どのような利点をもたらすのかを解説したい。 セッションを担当したMicrosoftのShawn Hargreaves氏（Dev Man
ChatRTX is a demo app that lets you personalize a GPT large language model (LLM) connected to your own content—docs, notes, images, or other data. Leveraging retrieval-augmented generation (RAG), TensorRT-LLM, and RTX acceleration, you can query a custom chatbot to quickly get contextually relevant answers. And because it all runs locally on your Windows RTX PC or workstation, you’ll get fast and
Say What? Chat With RTX Brings Custom Chatbot to NVIDIA RTX AI PCs Chatbots are used by millions of people around the world every day, powered by NVIDIA GPU-based cloud servers. Now, these groundbreaking tools are coming to Windows PCs powered by NVIDIA RTX for local, fast, custom generative AI. Chat with RTX, now free to download, is a tech demo that lets users personalize a chatbot with their ow
The Chrome team is thrilled to announce that WebGPU is now available by default in Chrome 113, which is currently in the Beta channel. WebGPU is a new web graphics API that offers significant benefits such as greatly reduced JavaScript workload for the same graphics and more than three times improvements in machine learning model inferences. This is possible due to more flexible GPU programming an
This list is illustrative of a GPU and vendor driver supporting all possible entrypoints/profiles using mesa 22.3. The actual capabilities reported in vaQueryConfigProfiles, vaQueryConfigEntrypoints , vaQueryConfigAttributes, VaQueryVideoProcPipelineCaps and others are dynamically queried from the underlying GPU and might vary between platforms and driver versions. The vainfo utility will list the
Mitsuba 3 is a research-oriented retargetable rendering system, written in portable C++17 on top of the Dr.Jit Just-In-Time compiler. It is developed by the Realistic Graphics Lab at EPFL. It can be compiled into many variants with optional derivative tracking, dynamic compilation via LLVM or CUDA, and various radiance representations (monochrome, RGB, or spectral light, potentially with polarizat
Warp is a Python framework for writing high-performance simulation and graphics code. Warp takes regular Python functions and JIT compiles them to efficient kernel code that can run on the CPU or GPU. Warp is designed for spatial computing and comes with a rich set of primitives that make it easy to write programs for physics simulation, perception, robotics, and geometry processing. In addition,
MicrosoftはWindows 10/11に、「GPUスケジューリング」機能を追加している。公式ブログによれば、WDDM（Windows Display Driver Model）2.7以降のドライバーを使用する環境で、メモリーの制御をGPUに委ねて遅延を低減し、性能を改善する機能である。 NVIDIA/AMDなどのeGPU（外付けGPU）を備えるPC環境と、対応デバイスドライバーがあれば利用可能。本機能はWindows 10 バージョン2004から搭載しているが、その頃はコロナ禍で気が滅入ってしまい、探究心が枯渇していた。最近は気持ちも安定し、逃避ではなく日々の楽しみとしてPCゲームをプレイしている。 そしてPCゲームのパフォーマンス調整を行っていた際、「GPUスケジューリング」の情報に出くわした次第だ。まずは確認方法から紹介する。 「Win」+「S」キー、もしくは「Win」+「Q」
Abstract You may have noticed a mysterious new optional feature called Hardware Accelerated GPU Scheduling appear in the advanced graphics settings page with the Windows 10 May 2020 update. The purpose of this blog is to give some background on this new feature and how we are introducing it. It is intended for folks curious about Windows internals. Remaining on the cutting edge of hardware innovat
Neural gigapixel images Neural SDF NeRF Neural volume We demonstrate near-instant training of neural graphics primitives on a single GPU for multiple tasks. In gigapixel image we represent an image by a neural network. SDF learns a signed distance function in 3D space whose zero level-set represents a 2D surface. NeRF [Mildenhall et al. 2020] uses 2D images and their camera poses to reconstruct a
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