GitHub - philipturner/metal-benchmarks: Apple GPU microarchitecture
This document thoroughly explains the M1 and M2 GPU architectures, focusing on GPGPU performance. Details include latencies for each ALU assembly instruction, cache sizes, and the number of unique instruction pipelines. This document enables evidence-based reasoning about performance on the Apple GPU, helping people diagnose bottlenecks in real-world software. It also compares Apple silicon to gen
Host your LLMs on Cloud Run | Google Cloud Blog
Run your AI inference applications on Cloud Run with NVIDIA GPUs Developers love Cloud Run for its simplicity, fast autoscaling, scale-to-zero capabilities, and pay-per-use pricing. Those same benefits come into play for real-time inference apps serving open gen AI models. That's why today, we’re adding support for NVIDIA L4 GPUs to Cloud Run, in preview. This opens the door to many new use cases
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ç±³NVIDIAã¯7月17日（ç¾åœ°æ™‚間）ã€ã€ŒNVIDIA Transitions Fully Towards Open-Source GPU Kernel Modulesã€ã¨é¡Œã—ãŸãƒ–ãƒã‚°è¨˜äº‹ã‚’公開ã—ã€GPUã®ã‚«ãƒ¼ãƒãƒ«ãƒ‰ãƒ©ã‚¤ãƒãƒ¢ã‚¸ãƒ¥ãƒ¼ãƒ«ã‚’完全ã«ã‚ªãƒ¼ãƒ—ンソース化ã—ã¦ã„ãã¨ç™ºè¡¨ã—ãŸã€‚ NVIDIAãŒæ–¹é‡è»¢æ›ã€ã‚«ãƒ¼ãƒãƒ«ãƒ‰ãƒ©ã‚¤ãƒãƒ¢ã‚¸ãƒ¥ãƒ¼ãƒ«ã‚’オープンソース化㸠NVIDIAã¯2022å¹´ã«ã‚‚Linuxå‘ã‘ã®GPUカーãƒãƒ«ãƒ¢ã‚¸ãƒ¥ãƒ¼ãƒ«ï¼ˆãƒãƒ¼ã‚¸ãƒ§ãƒ³R515）をオープンソースã¨ã—ã¦ãƒªãƒªãƒ¼ã‚¹ã—ã¦ãŠã‚Šã€ãƒ‡ãƒ¼ã‚¿ã‚»ãƒ³ã‚¿ãƒ¼å‘ã‘ã®ä¸€éƒ¨GPUã§åˆ©ç”¨ã§ããŸã€‚ã—ã‹ã—今回ã€R560をベースã«ã—ãŸæœ€æ–°ãƒ‰ãƒ©ã‚¤ãƒã®ãƒªãƒªãƒ¼ã‚¹ã‹ã‚‰ã‚ªãƒ¼ãƒ—ンソースGPUカーãƒãƒ«ãƒ¢ã‚¸ãƒ¥ãƒ¼ãƒ«ã¸ã®å®Œå…¨ç§»è¡Œã—ã¦ã„ãã¨ç™ºè¡¨ã€‚テストã§ã¯ã‚¯ãƒãƒ¼ã‚ºãƒ‰ã‚½ãƒ¼ã‚¹ã®ãƒ‰ãƒ©ã‚¤ãƒã¨åŒç‰ä»¥ä¸Šã®ãƒ‘フォーマンスを発æ®ã§ããŸã¨ã—ã¦ãŠã‚Šã€NVIDIAã¯éšæ™‚オープンソースã®GPUカーãƒãƒ«ãƒ¢ã‚¸ãƒ¥ãƒ¼ãƒ«ã«åˆ‡ã‚Š
NVIDIA to Acquire GPU Orchestration Software Provider Run:ai
Israeli startup promotes efficient cluster resource utilization for AI workloads across shared accelerated computing infrastructure. To help customers make more efficient use of their AI computing resources, NVIDIA today announced it has entered into a definitive agreement to acquire Run:ai, a Kubernetes-based workload management and orchestration software provider. Customer AI deployments are bec
Intro
infoThis documentation is a work-in-progress. Use.GPU is in alpha. warning_amberWebGPU is only available in certain browsers. Use.GPU is a set of declarative, reactive WebGPU legos. Compose live graphs, layouts, meshes and shaders, on the fly. It's a stand-alone Typescript+Rust/WASM library with its own React-like run-time. If you're familiar with React, you will feel right at home. It has a built
NVIDIA Releases Open-Source GPU Kernel Modules | NVIDIA Technical Blog
NVIDIA is now publishing Linux GPU kernel modules as open source with dual GPL/MIT license, starting with the R515 driver release. You can find the source code for these kernel modules in the NVIDIA/open-gpu-kernel-modules GitHub page This release is a significant step toward improving the experience of using NVIDIA GPUs in Linux, for tighter integration with the OS, and for developers to debug, i
New – EC2 Instances (G5) with NVIDIA A10G Tensor Core GPUs | Amazon Web Services
Like their predecessors, these instances are a great fit for many interesting types of workloads. Here are a few examples: Media and Entertainment – Customers can use G5 instances to support finishing and color grading tasks, generally with the aid of high-end pro-grade tools. These tasks can also support real-time playback, aided by the plentiful amount of EBS bandwidth allocated to each instance
GPU architecture types explained – RasterGrid
The behavior of the graphics pipeline is practically standard across platforms and APIs, yet GPU vendors come up with unique solutions to accelerate it, the two major architecture types being tile-based and immediate-mode rendering GPUs. In this article we explore how they work, present their strengths/weaknesses, and discuss some of the implications the underlying GPU architecture may have on the
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What's next for WebGPU  | Blog  | Chrome for Developers
OpenAI will start using AMD chips and could make its own AI hardware in 2026
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https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=802fed876e180f32c06ede4d1cc951ba44f79dd2
GitHub - NVIDIA/open-gpu-kernel-modules: NVIDIA Linux open GPU kernel module source
Intel beats AMD and Nvidia to become the first with full AV1 support with its new Arc GPUs
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GitHub - Rust-GPU/Rust-CUDA: Ecosystem of libraries and tools for writing and executing fast GPU code fully in Rust.
GitHub - intel/fastuidraw
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