A Gallup poll shows over 70% of Americans oppose AI data centers near their homes, threatening U.S. lead in AI against China. Local zoning battles and legitimate concerns over utility costs, water use…
A developer refactored Fortran code for GPU acceleration by replacing inline PPM slope computations with pure subroutines callable from do concurrent loops, improving code clarity and enabling better …
VLLM, a large-model inference serving framework, uses Python for control flow but pushes arithmetic into compiled C++ and CUDA kernels to avoid interpreter overhead. The Python/C++ boundary crossing i…
Google's TPU uses a systolic array architecture optimized for tensor algebra, offering higher throughput and energy efficiency than GPUs for dense matrix operations, but requires XLA compilation and i…
Google's Tensor Processing Units (TPUs) are specialized chips designed for neural network matrix multiplications, differing fundamentally from GPUs. Unlike GPUs, which evolved from graphics rendering,…
A developer using PyTorch and Lightning AI demonstrated automated neural network training with GPU acceleration. By setting the trainer's accelerator and devices to 'auto', Lightning automatically det…
DigitalOcean published a tutorial on June 19 demonstrating how to compress large language models using SparseGPT and Wanda pruning methods for GPU cloud deployment, targeting reduced inference costs a…
A developer describes running ~50 local AI agents on a single 6GB GPU by using a lock-based queue, an eviction monitor, a resource governor, and a model router. The system serializes GPU access so onl…
InfiniBand, a high-performance interconnect technology designed for Remote Direct Memory Access (RDMA), has become critical for AI training and inference workloads that require direct data movement be…
Micron Technology is set to report fiscal Q3 2026 earnings on June 24, projecting record revenue of $33.5B and a non-GAAP gross margin of 81%, more than double from a year ago, driven by surging deman…
HIVE Digital Technologies announced a CAD $3.5 billion AI gigafactory in the Greater Toronto Area, aiming to support Canada's goal of 850 MW of sovereign compute by 2030. The 320 MW facility, expected…
Nvidia demonstrated an agentic robotics system called ENPIRE that taught fleets of robots to perform dexterous tasks, including handing a GPU to another arm and positioning it over a motherboard. The …
MarkTechPost published a tutorial on building memory-efficient Transformers using xFormers, covering packed sequences, grouped-query attention, ALiBi, SwiGLU, and causal attention. The guide demonstra…
OpenAI spent $3.7 billion in Q1 2026, tripling its cash burn year-over-year, while revenue reached $5.7 billion. The company holds $73 billion in cash and securities after a $122 billion funding round…
A developer achieved 2678x faster matrix multiplication using a GPU with CUDA, demonstrating how parallel processing on thousands of GPU cores reduces the O(N³) complexity of sequential matrix multipl…
A technical analysis calculates the dollar cost per user for serving large language models at scale using napkin math, breaking down GPU resources, matrix multiplication costs, and attention mechanism…
A developer building Pixova's free AI image generator implemented an async job queue pattern to connect a Next.js frontend to a GPU inference endpoint, avoiding timeout issues from long-running HTTP c…
JAX's default_device context manager places arrays on the specified device but does not commit them, allowing JAX to move them to other devices. This caused array lookups to take over a second by trig…
Shrijith Venkatramana, developer of git-lrc, explains how kernel fusion reduces memory bandwidth bottlenecks in LLM inference. By combining multiple GPU operations into a single kernel, intermediate d…
Microsoft released Windows Subsystem for Linux (WSL) 3 as a beta preview at Build 2026, introducing paravirtualization to give Linux direct access to GPUs and NPUs without performance overhead. The up…