Keynotes
Torsten Hoefler (ETH, Zurich): Portable high-performance Python on CPUs, GPUs, and FPGAs
Abstract: 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 high performance. In this work, we present a workflow that retains Python's high productivity while achieving portable performance across different architectures. The workflow's key features are HPC-oriented language extensions and a set of automatic optimizations powered by a data-centric intermediate representation. We also define a set of around 50 benchmark kernels written in NumPy to evaluate and compare Python frameworks for their portability and performance. We show performance results and scaling across CPU, GPU, FPGA, with 2.47x and 3.75x speedups over previous-best solutions and the first-ever Xilinx and Intel FPGA results of annotated Python.
Bio: Torsten is a Professor of Computer Science at ETH Zürich, Switzerland. He is also a key member of the Message Passing Interface (MPI) Forum where he chairs the "Collective Operations and Topologies" working group. His research interests revolve around the central topic of "Performance-centric System Design" and include scalable networks, parallel programming techniques, and performance modeling. Torsten won best paper awards at the ACM/IEEE Supercomputing Conference SC10, SC13, SC14, SC19, EuroMPI'13, HPDC'15, HPDC'16, IPDPS'15, and other conferences. He published numerous peer-reviewed scientific conference and journal articles and authored chapters of the MPI-2.2 and MPI-3.0 standards. He received the Gordon Bell Prize, the Latsis prize of ETH Zurich, as well as both ERC starting and consolidator grants. Additional information about Torsten can be found on his homepage at htor.inf.ethz.ch. Nele Mentens (Leiden University, Netherlands AND KU Leuven, Belgium): FPGAs for security: three decades of academic research
Abstract: Since the existence of FPGA conferences, many research results have been published on the use of FPGAs for security purposes, mainly in the domains of cryptographic hardware, network security and trusted computing. FPGAs are being used as accelerators of cryptographic algorithms for authenticated encryption, digital signatures and key establishment. Especially in the quantum era, FPGAs are becoming prominent implementation platforms to support post-quantum crypto algorithms that rely on larger key sizes and larger memory and computation demands than traditional crypto algorithms. In network security, FPGAs are not only deployed to accelerate cryptographic algorithms, but also to facilitate network monitoring through high-speed search, sort and count functions. In trusted computing, FPGAs form a "patchable" alternative to ASICs, offering hardware-enabled control over the software running on a system. This talk summarizes the past three decades of academic research on the use of FPGAs for security and gives an outlook for future research directions.
Bio: Nele Mentens is a professor at Leiden University in the Netherlands and KU Leuven in Beligum. Her research interests are in the field of configurable computing and hardware security. She was/is the PI in around 25 finished and ongoing research projects with national and international funding. She serves/served as a program committee member of renowned international conferences on security and hardware design. She was the general co-chair of FPL'17 and she was/is the program chair of FPL'20, CARDIS'20, RAW'21, VLSID'22 and DDECS'23. She is (co-)author in around 150 publications in international journals, conferences and books. She received best paper awards and nominations at CHES'19, AsianHOST'17 and DATE'16. Nele serves as an associate editor for IEEE TIFS, IEEE CAS Magazine, IEEE S&P, and IEEE TCAD. Phil James-Roxby (AMD-Xilinx): Heterogenous Devices and You
Abstract: With the acquisition of Xilinx technology, AMD now can offer a massive range of truly heterogenous devices, from data center CPUs and GPUs, to coarse grain array-style AIE Engine devices as well as classic FPGA fabric. As a research community, it's hard to think of a better time to be involved in field-programmable logic.
In this talk, I will zoom in on the AIE Engine technology, and describe both the architecture, and tooling which make this fabric accessible to researchers, both in terms of application mapping, but also for compiler writers. The AIE Engine offers a unique mix of accessibility and performance, particularly for machine learning oriented workloads, and this talk will cover in detail the architectural features that lead to high performance applications, and also describe an open source toolflow based on MLIR which can be leveraged by both application developers, heterogenous runtimes, and higher level compiler stacks.
Finbarr O’Regan (Intel): It is Rocket Science: The Need for FPGAs in Low Earth Orbit Optical Inter-Satellite Links
Abstract: By 2030, tens of thousands of low earth orbit satellites will communicate with each other using optical inter-satellite links - the internet 2.0 backbone is being constructed 1000 km above our heads. FPGAs are key to this infrastructure. This talk will explore the advent of FPGA enabled coherent optics transceivers in space communications..
Bio: Dr. Finbarr O'Regan is a hardware engineer with Intel's Programmable Solutions Group CTO Office and is based in Cork on the south coast of Ireland. Finbarr's background in digital RTL design and implementation of signal processing systems. Finbarr started his career in S3, part of Philips Semiconductors in the mid-1990's before doing a PhD in signal processing in University College Dublin. Finbarr has given commercial training courses in IC design flows, Verilog and low power design all over the world. After graduating with his PhD, Finbarr was co-technical chair of the European Conference on Circuit Theory and Design in 2005 and subsequently started a company offering design and training courses. He worked as an IC design consultant for several companies before joining Intel in 2016.