Archive of posts tagged: Accelerators
Languages, Tools, and Techniques for Accelerator Design
FPGA-based accelerators have opened up a new frontier for accelerator design; instead of spending months building and fabricating silicon chips, programmers can buy a cloud instance to run custom hardware accelerators within hours. With the remarkable new hardware, there is a need for remarkable new software.
Point Clouds are Eating the World, One Application at a Time
A point cloud literally means a collection of points. One can think of a point as a sample of a surface, and each point is represented by the [x, y, z] coordinates in the 3D space. A point could have other attributes, such as normal, RGB color, albedo, and...
Multi-Modal On-Device AI: Heterogeneous Computing Once More?
What is Multi-modal AI? Prior research on developing on-device AI solutions have primarily focused on improving the TOPS (Tera Operations Per Second) or TOPS/Watt of AI accelerators by leveraging sparsity, quantization, or efficient neural network architectures...
The Future of Sparsity in Deep Neural Networks
Sparsity in Deep Neural Networks The key characteristic of deep learning is that accuracy empirically scales with the size of the model and the amount of training data. Over the past decade, this property has enabled dramatic improvements in the state of the art...Subscribe
