https://dasya.itu.dk/tags/fpga/ Recent content in FPGA on DASYA Hugo -- gohugo.io en-us © DASYA, IT University of Copenhagen Wed, 01 Feb 2023 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/delilah/ Wed, 01 Feb 2023 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/delilah/ The emergence of computational storage platforms like Delilah has transformed the data storage landscape, enabling new computing paradigms and facilitating data-intensive applications. Delilah is a cutting-edge computational storage platform developed by the IT University of Copenhagen. It runs on the Daisy OpenSSD and exposes an asynchronous computational storage protocol to the host, facilitated by eBPF, which orchestrates I/Os to the underlying storage mediums. However, Delilah’s quality assurance and regression testing in its specialised environment pose a significant challenge, necessitating cumbersome manual interactions. https://dasya.itu.dk/for-students/proposals/archive/inferenceinkvs/ Fri, 16 Apr 2021 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/inferenceinkvs/ (This project will be carried out in collaboration with Xilinx Research Labs in Dublin) Machine Learning operators are becoming increasingly commonly used in data management systems and, in this project, we will explore the challenges and benefits of integrating inference operators from FINN [1] within a so-called Smart Storage system [2]. Both the inference and data management aspects will be handled by an FPGA in order to provide small energy footprint and guarantee high access bandwidth at the same time (see details below). https://dasya.itu.dk/for-students/proposals/archive/ppkv/ Tue, 18 Aug 2020 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/ppkv/ Modern data analytics systems are composed of two types of nodes: compute and storage (e.g., Amazon S3, Redis, MongoDB, etc.). The storage nodes typically offer a key-value interface and are often used to store data encoded in a columnar format (e.g., Parquet files). Due to growing data sizes in datacenters, there is an increasing interest in using specialized hardware devices, namely Field Programmable Gate Arrays (FPGAs), to implement the storage nodes in an energy-efficient manner. https://dasya.itu.dk/for-students/projects/archive/smartssd/ Sat, 01 Feb 2020 00:00:00 +0000 https://dasya.itu.dk/for-students/projects/archive/smartssd/ An investigation of the performance of OCSSDs and stuff https://dasya.itu.dk/for-students/proposals/archive/fpga-based-hardware-acceleration/ Sun, 16 Jun 2019 00:00:00 +0000 https://dasya.itu.dk/for-students/proposals/archive/fpga-based-hardware-acceleration/ Field Programmable Gate Arrays are now an integral part of public cloud infrastructures. You can for example run customized FPGA instances on AWS. A project focuses on FPGA-based hardware acceleration at the level of an SSD Flash Translation Layer, at the level of a Database storage manager or at the level of the database client. You will be able to experiment with FPGAs in the lab and on AWS. We expect that it will be possible to collaborate with Samsung around SmartSSD.