🖥 GPUs - emschwartz · Scour

Taming GPU Underutilization via Static Partitioning and Fine-grained CPU Offloading ⚙️Mechanical Sympathy

arxiv.org·15h

AI Training Goes Off the Grid With Solar Homes and Spare GPUs 🌐Distributed systems

spectrum.ieee.org

·3d·Hacker News

Integrate Physical AI Capabilities into Existing Apps with NVIDIA Omniverse Libraries ✨Gemini

developer.nvidia.com·2d

A developer’s guide to architecting reliable GPU infrastructure at scale 🏗️LLM Infrastructure

cloud.google.com·21h

Nvidia can't have every data center workload 🤖AI

runtime.news·20h

Nvidia Pascal GPUs debuted 10 years ago today, best known for the GTX 1060 and GTX 1080 Ti — architecture kicked off with the Tesla P100 🤖AI

tomshardware.com

·5d

CUDA Programming for NVIDIA H100s ⚡Hardware Acceleration

freecodecamp.org·20h

How Nvidia learned to embrace the light in its quest for scale 📊Model Serving Economics

theregister.com·5d·Hacker News

janit/viiwork: LLM inference load balancer optimized for AMD Radeon VII GPUs 🏗️LLM Infrastructure

github.com·5d·Hacker News

Fine-Grained Power and Energy Attribution on AMD GPU/APU-Based Exascale Nodes ⚡Hardware Acceleration

arxiv.org·2d

What is an AI Native Cloud? 🆕New AI

together.ai·3d

pmady/keda-gpu-scaler: KEDA External gRPC Scaler for GPU workloads — native NVML metrics via DaemonSet, no Prometheus required 🏗️LLM Infrastructure

github.com·3d

Foundry: Template-Based CUDA Graph Context Materialization for Fast LLM Serving Cold Start 🏗️LLM Infrastructure

arxiv.org·1d

GTaP: A GPU-Resident Fork-Join Task-Parallel Runtime with a Pragma-Based Interface ⚡Hardware Acceleration

arxiv.org·2d

ai-infos/vllm-gfx906-mobydick: A high-throughput and memory-efficient inference and serving engine for LLMs - Optimized for AMD gfx906 GPUs, e.g. Radeon VII / MI50 / MI60 🏗️LLM Infrastructure

github.com·4d·r/LocalLLaMA

Wattlytics: A Web Platform for Co-Optimizing Performance, Energy, and TCO in HPC Clusters ⚡Systems Performance

arxiv.org·15h

Running AI Workloads on Rack-Scale Supercomputers: From Hardware to Topology-Aware Scheduling 🏗️LLM Infrastructure

developer.nvidia.com·3d

Blink: CPU-Free LLM Inference by Delegating the Serving Stack to GPU and SmartNIC 🏗️LLM Infrastructure

arxiv.org·15h

Minos: Systematically Classifying Performance and Power Characteristics of GPU Workloads on HPC Clusters ⚡Systems Performance

arxiv.org·3d

Characterizing WebGPU Dispatch Overhead for LLM Inference Across Four GPU Vendors, Three Backends, and Three Browsers 🏗️LLM Infrastructure

arxiv.org·4d·Hacker News

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