Researchers from MIT and NVIDIA have developed two techniques that accelerate the processing of sparse tensors, a type of data structure that’s used for high-performance computing tasks. The ...
Artificial intelligence (AI) workloads, spanning deep learning training, real-time inference, graph neural networks, and generative models, continue to ...
A new technical paper titled “Modeling and Optimizing Performance Bottlenecks for Neuromorphic Accelerators” was published by researchers at Harvard University, Politecnico di Torino, Intel, LMU ...
What is Femtosense’s SPU-001 AI accelerator. How sparsity and small-footprint accelerators reduce space and power requirements. Not every microcontroller can handle artificial-intelligence and machine ...
A technical paper titled “A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators” was published by researchers at Argonne National Laboratory, State University of New York ...
We have said it before, and we will say it again right here: If you can make a matrix math engine that runs the PyTorch framework and the Llama large language model, both of which are open source and ...
As ZDNET's Radhika Rajkumar details, R1's success highlights a sea change in AI that could empower smaller labs and researchers to create competitive models and diversify available options. Its ...
New computational techniques, 'HighLight' and 'Tailors and Swiftiles,' could dramatically boost the speed and performance of high-performance computing applications like graph analytics or generative ...
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