Archive of posts tagged: Cloud computing
5 Guidelines for Research in ML for Systems
It was more than 10 years ago that I first started studying machine learning (ML). Serendipitously, I ended up leveraging ML techniques developed for biological sequence analysis for optimizing storage systems. In the recent past, I have focused on optimizing and...
Computation Pushdown across Layers in the Storage Hierarchy
The memory and storage hierarchy deepens in modern systems. To mitigate the low performance of memory/storage devices at the bottom of the hierarchy, near-data processing has been studied across different memory and storage devices as a means to reduce access latency...
Architectures and Security of FPGA-Accelerated Cloud Computing
FPGAs in Cloud Computing The availability of Field Programmable Gate Arrays (FPGAs) in cloud datacenters has opened up new ways to improve application performance by letting users write their own custom hardware accelerators that they can realize on the FPGAs....
Rethinking Data Storage and Preprocessing for ML
Machine learning (ML) — and in particular deep learning — applications have sparked the development of specialized software frameworks and hardware accelerators. Frameworks like PyTorch and TensorFlow offer a clean abstraction for developing and running...Subscribe
