Search headlines, summaries and articles to connect the dots.
Enhancements to OpenCL support in llama.cpp include adding new kernel functions for quantized matrix operations, improving small-n MoE GEMV performance across multiple quantization types, optimizing Adreno GPU kernel floor settings, renaming functions for clarity, and disabling bin FA for small verification batches.
How vLLM migrated its CUDA build and compiled dependencies to the LibTorch Stable ABI, enabling compatible PyTorch upgrades without rebuilding vLLM.
Chris Alexiuk has a simple rule about open source AI: If you believe in it, be loud about it. “We should be shouting about this technology from the rooftops,” said Alexiuk, a Toronto-based senior product research engineer in deep learning at NVIDIA who specializes in making open large language models (LLMs) practical for working developers. […]
In distributed AI workloads, a single error can produce a cascade of symptoms. A GPU or fabric event may surface as NCCL errors on other ranks, scheduler state...
STCO for heterogeneous design; physical AI interactions; signing off AI-generated designs; workload profile analysis. The post Blog Review: Oct. 28 appeared first on Semiconductor Engineering.
opencl: initial support for q3_k (#31172) * opencl: add q3_k AOS mv * opencl: add q3_k SOA mv and tiled mm * opencl: add q3_k noshuffle gemm/gemv for adreno * opencl: add q3_k dp4a gemm for adreno Co-authored-by: Hongqiang Wang * opencl: tune q3_k kernels for adreno Co-authored-by: Hongqiang Wang --------- Co-authored-by: Hongqiang Wang **Website:** - **Attestations:** - **macOS/iOS:** - [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/b11918/llama-b11918-bin-macos-arm64.tar.gz) - macOS Apple Silicon (arm64, KleidiAI enabled) [DISABLED](https://github.com/ggml-org/llama.cpp/pull/23780) - [macOS Intel (x64)](https://github.com/ggml-org/llama.cpp/releases/download/b11918/llama-b11918-bin-macos-x64.tar.gz) - [iOS XCFramework](https://github.com/ggml-org/ll
A cross-section of the MIT community convened discussions on topics ranging from data centers and super pollutants to agriculture and education.
Today we are taking a look at ASRock's high-end Radeon AI inference card for workstations, the Creator Radeon AI Pro R9700. With 32GB of RAM and a $1700 price tag, the card is a highly affordable way to fill out a workstation for local AI inference The post ASRock Creator Radeon AI Pro R9700 Review: Workstation Inference, AMD Style appeared first on ServeTheHome.
Eight years ago, chipmaker Marvell Technology Inc. decided to play leapfrog with nanometers, and its trajectory has been steadily upward since. In semiconductor manufacturing, nanometer designations identify generations of chipmaking technology, known as process nodes, rather than the exact physical dimensions of transistors. Advanced process nodes generally enable greater transistor density and improvements in performance […] The post Marvell’s early chipmaking gamble pays off amid AI demand appeared first on SiliconANGLE.
vulkan: Add a larger tile size for conv3d (coopmat2 only) (#29920) * vulkan: Add a larger tile size for conv3d (coopmat2 only) This adds a larger tile size, in practice it is only for coopmat2 where we don't need shared memory to store the output (would use more than 64KB). Add some additional representative backend tests. At least, this is what codex came up with from looking at sd.cpp Wan VAE. * only apply large tile size for newer driver versions **Website:** - **Attestations:** - **macOS/iOS:** - [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/b11877/llama-b11877-bin-macos-arm64.tar.gz) - macOS Apple Silicon (arm64, KleidiAI enabled) [DISABLED](https://github.com/ggml-org/llama.cpp/pull/23780) - [macOS Intel (x64)](https://github.com/ggml-org/llama
Continue enables you to easily create your own coding assistant directly inside Visual Studio Code and JetBrains with open-source LLMs.
