See how we created a form of invisible surveillance, who gets left out at the gate, and how we’re inadvertently teaching the ...

Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models ...

Abstract: This work bridges the gap between multi-GPU computing and high-productivity, performance-portable programming solutions. Our goal is to enhance scientific applications with a productive and ...

In Pyper, the task decorator is used to transform functions into composable pipelines. Let's simulate a pipeline that performs a series of transformations on some data.

While analysts monitor a handful of charts, AI systems simultaneously track thousands of data points across hundreds of trading pairs, identifying invisible patterns and correlations. More critically, ...

Classiq 1.0 is designed for enterprise quantum R&D groups, algorithm developers, researchers and engineering teams that need to connect classical logic and constraints to quantum models and carry that ...

This desktop app for hosting and running LLMs locally is rough in a few spots, but still useful right out of the box.

Bengaluru-based Sarvam AI has outperformed Google’s Gemini and OpenAI’s ChatGPT in Indian language benchmarks, showcasing locally trained models for documents, speech, and low-bandwidth use across ...

Abstract: We present a hybrid GPU programming curriculum that allows students to choose between Python (Numba) and C++ (CUDA), supporting language flexibility in a distance-learning context. The ...

NVIDIA's new CUDA Tile IR backend for OpenAI Triton enables Python developers to access Tensor Core performance without CUDA expertise. Requires Blackwell GPUs. NVIDIA has released Triton-to-TileIR, a ...

We took this version of HeCBench and are modifying it to build the CUDA and OMP codes to gather their roofline performance data. So far we have a large portion of the CUDA and OMP codes building ...