gpu

One interface for cloud GPUs. Point Compute at a Python function. It provisions a fresh machine for the job and streams output to your terminal. When the run ends, Compute confirms termination and puts provider usage and the platform fee on one receipt. A run, end to end $ compute run simple_mlp.py::train --gpu H100 - estimaterate locked · confirmation required - provisionfresh H100-SXM requested…

Compute with Hivenet gives AI, research, simulation, and rendering teams dedicated RTX 4090 and RTX 5090 GPU instances without buying hardware or managing HPC clusters. Learn how it supports practical high-performance computing with full VRAM, transparent pricing, persistent usage, and human support.

A field report on serving Google's Gemma 4 E2B on AWS EC2 **G5g * — a Graviton2 (aarch64) host with an NVIDIA T4G (Turing, SM 7.5) GPU. Three obstacles: an arch list nobody publishes for this combination, a version floor that only the newest vLLM clears, and 64 KiB of shared memory that stops the model dead. Plus the seven things I documented wrong before I had a box.* Model google/gemma-4-E2B-it…

Before graphics processing units (GPUs) became the powerhouse chips driving modern video games, scientific simulations, and artificial intelligence, computer graphics were slow, blocky, and severely limited. Understanding how we got from simple glowing dots to today's hyper-realistic 3D worlds requires looking back at a few key breakthroughs in computing history. Part 1: In the Beginning — Legacy…

TLDR: I’ve built Phobos, a tiny kernel language inspired by Triton. It lowers to PTX and runs on NVIDIA GPUs. It achieves acceptable performance at 76% of cuBLAS SGEMM GFLOP/s on a 2080 SUPER (or 74% of the theoretical GFLOP/s peak). Phobos maps naturally to a distributed tile-DAG design. I only validated the cluster prototype on a single machine; there are no multi-node benchmarks here. This was…

The system moves high-speed detector data directly to GPUs , allowing scientists to examine more information before it is filtered out or sent for storage. NVIDIA DAQIRI connects high-speed scientific instruments and sensors directly with GPU-powered computing systems for real-time data processing. Image credit: NVIDIA NVIDIA has introduced DAQIRI, a high-speed data system designed to process inf…

CUDA for AMD Lemonade, Intel Arc Pro Linux Gains, XPU Manager 2.0 Today's Highlights Today's top GPU news highlights include AMD's Lemonade SDK gaining NVIDIA CUDA support, significant performance improvements for Intel Arc Pro GPUs on Linux 7.1, and the major 2.0 overhaul of Intel's XPU Manager for better GPU management on both Windows and Linux. AMD's Lemonade SDK For Local AI Adds NVIDIA CUDA …

This article was originally published on runaihome.com TL;DR : The RTX 5060 delivers GDDR7's 448 GB/s bandwidth at $299 — the same memory throughput as the 5060 Ti — and runs 7B–8B models at a solid 30 tok/s. The problem: 8GB VRAM is a hard ceiling with no exceptions. No 13B, no long context, no FLUX.1. If you run local LLMs beyond casual chatting, skip this card. RTX 5060 8GB RTX 5060 Ti 16GB Us…

I already had an RTX 4080. 16GB of VRAM. Good enough for gaming, not good enough for the models I wanted to run locally. The next step up in GPU land is either spend a fortune on a card with more VRAM, or find another way. I found another way. I bought a datacenter GPU that doesn’t even have a normal PCIe connector, stuck it in my gaming PC with an adapter, and now I have 32GB of VRAM across two …

GPU Hardware & Driver Update: RTX 5090 Benchmarks, llama.cpp MTP, Windows 11 Fix Today's Highlights This week's top GPU news features practical performance optimization on NVIDIA's RTX 5090, a critical driver fix for Windows 11 users, and deep dives into multi-tensor processing for local LLM inference. Testing llama.cpp MTP Support on RTX 5090 (r/LocalLLaMA) Source: https://reddit.com/r/LocalLLaM…

RTX 5080 Launched, Rust for CUDA, & LLM GPU Scheduling Deep Dive Today's Highlights This week's top GPU news highlights a new GeForce RTX 5080 variant, alongside advancements in GPU programming tools and deep dives into LLM optimization. Developers can now explore a Rust-to-PTX compiler for CUDA, while a new article sheds light on custom GPU scheduling for large language models. Palit Unveils GeF…

Chicago startup Newtonian Standard says it has identified a memory behavior in NVIDIA GPUs that could serve as the foundation for a new kind of hardware-level security. J.P. O’Donnell, the company’s founder and a former Okta engineer, says he spent 18 months characterizing the behavior across NVIDIA Turing, Lovelace and Blackwell GPU architectures. The company… The post A startup says it found hi…

In an age of constrained compute, learn how to optimize GPU efficiency through understanding architecture, bottlenecks, and fixes ranging from simple PyTorch commands to custom kernels. The post A Guide to Understanding GPUs and Maximizing GPU Utilization appeared first on Towards Data Science .

A new technical paper, “SwarmIO: Towards 100 Million IOPS SSD Emulation for Next-generation GPU-centric Storage Systems,” was published by KAIST. Abstract “GPU-initiated I/O has emerged as a key mechanism for achieving high-throughput storage access by leveraging massive GPU thread-level parallelism, while recent industry trends point toward SSDs optimized for ultra-high random-read IOPS. Togethe…

The GPU market in 2025 has finally stabilized after years of volatility, but the complexity of choosing the right hardware has only increased. Between the rise of frame generation technologies, the increasing demand for VRAM in modern titles, and the divergent paths of NVIDIA and AMD, a simple price to performance calculation is no longer sufficient. This guide cuts through the marketing fluff to…