77 stories
The Local LLM Lab — Part 10 One controlled experiment. One number. One verdict. Every homelab has a moment like this: the GPU is at 100%, the fan is screaming, and you have no idea which of the twenty services on the box is doing it.
The increasing demand for GPU-accelerated machine learning inference has exposed limitations in centralized GPU infrastructures, including high cost, limited elasticity, and long wait times under resource constraints.
In PC DIY it might still be worth challenging convention, as TrashBench shows with his GPU hotspot getting up to 19C cooler.
A Jiangsu chip startup founded by former Nvidia GPU architect Xu Feixiang is building Y10, a physical AI processor aiming for sub-millisecond closed-loop latency, with an FPGA platform due this year.
We crunched the numbers: deploying 4x A100s on Runpod's GPU cloud can save over $124,000 versus an on-prem cluster across 3 years. Learn why cloud beats.
Runpod’s new REST API lets you manage GPU workloads programmatically, launch, scale, and monitor pods without ever touching the dashboard.
SPEC has released version 15.0.1 of SPECviewperf Linux Edition, bringing a slew of upgrades and official Arm support to Linux's key workstation graphics benchmark suite.
Building a cluster scheduler to prioritize high-impact research while maintaining full occupancy
We explain how Ai2’s new GPU scheduler uses time budgets, fair-share allocation, and time-slicing to prioritize high-impact research, shorten queue waits, and keep GPUs busy.
In recent years, persistent homology has seen rapid adoption in deep learning, yet its computation remains a major bottleneck in network training. This paper introduces TopoGPU, a GPU streaming pipeline that computes persistence diagrams of cubical complexes induced by 2D and 3D images.
The GPU giant released a fix for the flaw, tracked as CVE-2026-47483
A reference architecture for securely sharing one Amazon SageMaker HyperPod EKS cluster across multiple teams, using AWS IAM Identity Center for authentication, per-team SageMaker Domains and Kubernetes namespaces for isolation, HyperPod Task Governance for fairness, and namespace-level cost…
AI agents can now write CUDA kernels that outperform PyTorch—but proving those speedups are real is the harder problem. I put them to the test on an NVIDIA DGX Spark and found that benchmark design matters just as much as the code.
Write-up + demo: https://drksci.com/labs-phosphene So this started as a bit of a gripe. Modern terminal renderers are seriously impressive and seriously complicated. GPU glyph atlases, texture caches, custom shaders, HarfBuzz shaping, ligatures, damage tracking, grid diffing, dirty-row uploads.
Nvidia's RTX 5090 now costs $7,000. Or so near to it that it makes no difference. So if you were hoping to buy one in the quest to build a PC, you're out of luck. You're much better off just grabbing a pre-built PC with one inside.
Mistral AI SAS today opened access to Mistral Large 4, its most capable large language model to date. On launch, the LLM is available in public preview through the company’s cloud platform. Mistral plans to release the model’s weights later this month.
GPU applications increasingly need networking and data movement to behave like first-class GPU-controlled operations rather than host-driven services. When the...
On October 2, 2026, we completed the second live verification of the x402 pay-per-job service on Kilawatt Cloud. In Wave 1, every request went to a single supplier. This time we sent each request to a different one, so every supplier could be evaluated on its own. As before: no simulation.
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