byteLAKE and Avnet Silica showing Machine Learning Solutions at MLPrague
UPDATE (2020–03–11): Due to coronavirus we had to postpone the conference. We will announce the new date soon. At the same time all projects at byteLAKE are secured and we are working on few exciting extras to bring for you to the conference at some later time.
Looking for practical applications in the fields of Artificial Intelligence, Machine Learning or Deep Learning? Well, there is only one way to experience all of these as early as at the beginning of spring 2020: MLPrague.
It’s a 3-day event, happening in Prague (Czech Republic) in the beautiful Czech Philharmonic, the Rudolfinum. Some numbers speaking about the event: 900 attendees, 45 speakers, 10 workshops and yes! 2 parties! Hopefully this little “pet” with a vicious name coronavirus will not become a visitor and be eventually fired from this world…
Anyway, this year byteLAKE together with Avnet Silica have prepared a line-up of exciting demos. Also, and this is even more exciting, we have been accepted as speakers during this prestigious event!
We will showcase an AI accelerated multi-camera solution, and you will also have the opportunity to take a closer look at the Alveo workstation with byteLAKE’s CFD suite — a collection of fluid dynamics algorithms, highly optimized for Xilinx Alveo FPGA powered architectures.
On Saturday (16:00), byteLAKE’s CTO Krzysztof Rojek will give a presentation about Exchange rate estimation of cryptocurrencies with FPGA and GPU accelerators.
“Predicting cryptocurrency exchange rates is a significant issue in the economic market. A cryptocurrency is a digital asset designed to work as a medium of exchange that uses strong cryptography to secure financial transactions, control the creation of additional units, and verify the transfer of assets. In current world, it gives serious effect on worldwide economic aspects. For the last years we observe an intensive development of accelerated computing platforms. Although current trends indicate a well-established position of GPU devices in the HPC environment, FPGA aspires to be an alternative solution to offload the CPU computation. This work presents a machine learning-based approach to predict the exchange rate of current cryptocurrencies in order to develop a better understanding on its price. Our goal is to compare the possibilities of utilization of platforms equipped with the FPGA and GPU accelerators. We focus on the set of aspects taking into account adaptation of ML methods to the accelerators, performance of the proposed solutions, accuracy of results, as well as the energy consumption of the platforms. This work investigates the most advanced accelerators used in the ML solutions, including NVIDIA Tesla V100 GPU, and Xilinx Alveo U250 FPGA. The exchange rate estimation is based on ML models using Long Short-Term Memory, as well as Neural Network with Hidden Layers”.
See you at MLPrague! Do not forget to follow us on social media channels to get all the updates. Feel free to reach out to us to set up 1:1 discussions. All contacts and links at www.byteLAKE.com.
Visit this link to get a discount code for tickets: https://www.avnet.com/wps/portal/silica/resources/training-and-events/event/ml-prague
