Archive of posts tagged: Machine Learning
Hardware Acceleration Opportunities for Machine Learning on Massive Datasets
Data management research has recently been paying more attention on how to run machine learning algorithms efficiently on massive datasets. This blog post focuses on three recent research papers that identify time-consuming data processing operations in machine...
Why the GPGPU is Less Efficient than the TPU for DNNs
The GPGPU’s massive multithreading is unnecessary for DNNs, and imposes performance, area, and energy overheads. By avoiding such multithreading, the TPU is more efficient.
The Future in Visual Computing: Research Challenges
The tremendous growth in visual computing is fueled by the rapid increase in deployment of visual sensing (e.g. cameras) in many usages ranging from digital security/surveillance and automated retail (e.g. smart cameras & analytics) to interactive/immersive...
DNN Accelerator Architecture – SIMD or Systolic?
While the concept of hardware acceleration has been around for a while, DNN accelerators are perhaps the first to see the light of commercial adoption due to the AI/ML wave. Giant software corporations, veteran hardware companies, and a plethora of start-ups have...Subscribe
