Session Chair: Christian Plessl
Python has become the de-facto language for scientific computing. Programming in Python is highly productive, mainly due to its rich science-oriented software ecosystem built around the NumPy module. As a result, the demand for Python support in High Performance Computing (HPC) has skyrocketed. However, the Python language itself does not necessarily offer...
In the past few years, HPC computing has also gained importance in groups of users that in the past did not belong to the classic HPC users, not least because of the increasing popularity of Deep Learning. However, the use of HPC systems has not changed for a long time: Access is often still via the console, jobs are written in Bash scripts - and the most popular programming languages are...
High-Performance Computing (HPC) is at an inflection point in its evolution. General-purpose architectures approach limits in terms of speed and power/energy, requiring the development of specialized architectures to deliver accelerated performance. Additionally, the arrival of new user communities and workloads---including machine learning, data analytics, and quantum simulation---increases...
With the advancement of HLS technology, FPGA is finally drawing attention as a power-efficient accelerator device. Unlike GPUs, the computation pipeline and FPGA-to-FPGA interconnection can be tightly coupled on FPGAs because they have high-speed serial transceivers on the device itself. The direct connection between computation and network encourages building FPGA clusters with direct...
This work proposes a novel dataflow architecture for Smith-Waterman Matrix-fill and Traceback stages, which are at the heart of short- read alignment on NGS data. The FPGA accelerator is coupled with radical software restructuring to widely-used Bowtie2 aligner to deliver end-to-end speedup while preserving accuracy.
Talk to the speakers of the PhD Forum in Breakout-Rooms.
Real-time object detection, recognition and tracking is essential for safety critical applications such as autonomous vehicles as well as video analytics, where critical information should be extracted from video streams for applications such as surveillance for security, health and safety monitoring in healthcare and industry, intelligent transportation systems and smart cities. To reduce the...
Gigantic rates of data production in the era of Big Data, Internet of Thing (IoT), and Smart Cyber Physical Systems (CPS) pose incessantly escalating demands for massive data processing, storage, and transmission while continuously interacting with the physical world under unpredictable, harsh, and energy-/power-constrained scenarios. Therefore, such systems need to support not only the...
