All times shown in PDT (UTC-7)

Sunday, April 28

All Sunday events are at the Sanford Consortium for Regenerative Medicine in the Roth Auditorium and the Bella Vista Caffe Terrace

RISC-V in Custom Computing Machines
3:30 – 5:00 PM PDT
Roth Auditorium


  • David Donofrio, Lawrence Berkeley National Laboratory
  • Farzad Fatollahi-Fard, Lawrence Berkeley National Laboratory
  • John Leidel, Tactical Computing Labs

David, Farzad and John, leading researchers in RISC-V architecture, will present an overview of the processor from the FCCM perspective. The RISC-V community continues to grow and the widespread adoption of RISC-V based cores has led to well supported hardware implementations combined with feature-complete software toolchains.  These open source designs rival, and are often superior to, commercial soft core offerings.  Topics to be discussed include:

  • Advantages/disadvantages compared to vendor provided soft processors
  • The various RISC-V flavors and configuration options
  • How to extend the instruction set to create custom instructions in the FPGA fabric
  • Compiler tool chain and how to splice or download RISC-V programs onto the FPGA
  • How to run standalone programs
  • Examples or applications of RISC-V use in FPGA designs

Soft Processor Panel
5:30 – 7:00 PM PDT
Roth Auditorium

The panelists will offer their viewpoints on the roles and management of soft processor cores in custom computing machines.  Topics include core microarchitectures, configurability and options, cache and memory hierarchy, interaction of soft and hard processors, interfaces to hard and soft IP blocks, compiler and debug tools, software stack and run time.


  • Rob Aitken, ARM
  • Mike Butts, Compute Forest
  • Jan Gray, Gray Research
  • Guy Lemieux, University of British Columbia and Founder, CEO of VectorBlox
  • Ron Minnich, Google
  • Lesley Shannon, Simon Fraser University
  • Ted Speers, Microsemi
  • Stephen Neuendorffer, Xilinx

Sunset Reception
7:00 – 8:30 PM PDT
Bella Vista Caffe Terrace

Monday, April 29

Technical Program
Qualcomm Institute Auditorium

TimeSession Title (Chair)Presentation TitleAuthors
8:30OpeningOpening SessionRyan Kastner, André DeHon
(Jason Cong)
HoF induction, KeynoteRahul Razdan
9:45Open Source Tools
(Lesley Shannon)
Yosys+nextpnr: an Open Source Framework from Verilog to Bitstream for Commercial FPGAs (short)David Shah, Eddie Hung, Clifford Wolf, Miodrag Milanovic, Serge Bazanski and Dan Gisselquist
EFCAD – an Embedded FPGA CAD Tool Flow for Enabling On-Chip Self-Compilation (short)Khoa Pham, Malte Vesper, Dirk Koch and Eddie Hung
Maverick: A Stand-alone CAD Flow for Partially Reconfigurable FPGA ModulesDallon Glick, Jesse Grigg, Brent Nelson and Michael Wirthlin
10:15Morning Break and Poster Session 1: ToolsDetails
11:00Machine Learning 1
(Ro Cammarota)
An Efficient Hardware Accelerator for Sparse Convolutional Neural Networks on FPGAsLiqiang Lu, Jiaming Xie, Ruirui Huang, Xiaoyuan Cui, Jiansong Zhang, Wei Lin and Yun Liang
LUTNet: Rethinking Inference in FPGA Soft LogicErwei Wang, James Davis, Peter Cheung and George Constantinides
PIR-DSP: An FPGA DSP-block Architecture for Multi-Precision Deep Neural NetworksSeyedramin Rasoulinezhad, Hao Zhou, Ling Li Wang and Philip H.W. Leong
Towards Efficient Deep Neural Network Training by FPGA-based Batch-level ParallelismCheng Luo, Man-Kit Sit, Hongxiang Fan, Shuanglong Liu, Wayne Luk and Ce Guo
(Eli Bozorgzadeh)
CRoute: A Fast High-Quality Timing-driven Connection-based FPGA RouterDries Vercruyce, Elias Vansteenkiste and Dirk Stroobandt
RapidRoute: Fast Assembly of Communication Structures on FPGAs (short)Leo Liu, Jay Weng and Nachiket Kapre
Generic Connectivity-Based CGRA Mapping via Integer Linear ProgrammingMatthew J. P. Walker and Jason H. Anderson
LAMDA: Learning-Assisted Multi-Stage Autotuning for FPGA Design Closure (short)Ecenur Ustun, Shaojie Xiang, Jinny Gui, Cunxi Yu and Zhiru Zhang
Memory Mapping for Multi-Die FPGAsNils Voss, Pablo Quintana, Oskar Mencer, Wayne Luk and Georgi Gaydadjiev
Impact of FPGA Architecture on Area and Performance of CGRA OverlaysIan Taras and Jason Anderson
An FPGA-based BWT Accelerator for Bzip2 Data Compression (short)Mau-Chung Frank Chang, Jason Cong, Zhenman Fang and Weikang Qiao
3:10Afternoon Break and Poster Session 2: Neural Networks and Vision Details
3:50Applications 1
(Christophe Bobda)
π-BA: Bundle Adjustment Acceleration on Embedded FPGAs with Co-observation OptimizationShuzhen Qin, Qiang Liu, Bo Yu and Shaoshan Liu
Deep Packet Inspection in FPGAs via Approximate Nondeterministic AutomataMilan Ceska, Vojtěch Havlena, Lukas Holik, Jan Korenek, Ondrej Lengal, Denis Matousek, Jiří Matoušek, Jakub Semric and Tomas Vojnar
Active Stereo Vision with High Resolution on an FPGAMarc Pfeifer, Philipp Scholl, Rainer Voigt and Bernd Becker
Hardware Acceleration of Long Read Pairwise Overlapping in Genome Sequencing: A Race Between FPGA and GPULicheng Guo, Ka Cheong Jason Lau, Zhenyuan Ruan, Peng Wei and Jason Cong
Processor Assisted Worklist Scheduling for FPGA Accelerated Graph Processing on a Shared Memory PlatformYu Wang, James Hoe and Eriko Nurvitadhi
6:00Demo Night at Scripps ForumDetailsGrace Zgheib
9:00End of Demo Night

Poster Session 1: Tools

Automated Tool and Runtime Support for Fine-grain Reconfiguration in Highly Flexible Reconfigurable SystemsRafael Zamacola, Alberto García Martínez, Javier Mora, Andrés Otero and Eduardo de La Torre
AutoPhase: Compiler Phase-Ordering for High-Level Synthesis with Deep Reinforcement LearningQijing Huang, Ameer Haj-Ali, William Moses, John Xiang, Ion Stoica, Krste Asanovic and John Wawrzynek
Efficient FPGA Floorplanning for Partial Reconfiguration-Based ApplicationsNorbert Deak, Octavian Creţ and Horia Hedeşiu
Towards Prototyping and Acceleration of Java Programs onto Intel FPGAsMichail Papadimitriou, Juan Fumero, Athanasios Stratikopoulos and Christos Kotselidis
Sonar: Writing Testbenches through PythonVarun Sharma, Naif Tarafdar and Paul Chow
Raparo: Resource-Level Angle-Based Parallel Routing for FPGAsMinghua Shen and Nong Xiao
Automated acceleration of dataflow-oriented C applications on FPGA-based systemsFrancesco Peverelli, Marco Rabozzi, Salvatore Cardamone, Emanuele Del Sozzo, Alex J. W. Thom, Marco Domenico Santambrogio and Lorenzo Di Tucci
Automated Design Space Exploration and Roofline Analysis for FPGA-based HLS ApplicationsMarco Siracusa, Marco Rabozzi, Emanuele Del Sozzo, Marco Domenico Santambrogio and Lorenzo Di Tucci
Formalizing loop-carried dependencies in Coq for high-level synthesisFlorian Faissole, George A. Constantinides and David Thomas

Poster Session 2: Neural Networks and Vision

Exploring the Random Network of Hodgkin and Huxley Neurons with Exponential Synaptic Conductances on OpenCL FPGA PlatformZheming Jin and Hal Finkel
A Scalable OpenCL-Based FPGA Accelerator For YOLOv2Ke Xu, Xiaoyun Wang and Dong Wang
Model-Extraction Attack against FPGA-DNN Accelerator Utilizing Correlation Electromagnetic AnalysisKota Yoshida, Takaya Kubota, Mitsuru Shiozaki and Takeshi Fujino
SimBNN: A Similarity-Aware Binarized Neural Network Acceleration FrameworkCheng Fu, Shilin Zhu, Huili Chen, Farinaz Koushanfar, Hao Su and Jishen Zhao
KPynq: A Work-Efficient Triangle-Inequality based K-means on FPGAYuke Wang, Zhaorui Zeng, Boyuan Feng, Lei Deng and Yufei Ding
A High Throughput and Energy-Efficient Retina-Inspired Tone Mapping ProcessorLili Liu, Xiaoqiang Xiang, Yuxiang Xie, Yongjie Li, Bo Yan and Jun Zhou
An OpenCL-based Acceleration for Canny Algorithm Using a Heterogeneous CPU-FPGA PlatformSamah Rahamneh and Lina Sawalha

Demo Night
6:00 – 8:30 PM PDT

Scripps Forum

Demo Night is an opportunity for people to show off their latest and greatest systems, tools, and technologies in a relaxed atmosphere. See the latest technology from industry, meet with the leading FCCM researchers, demonstrate the latest and greatest research, and receive early feedback on work in progress.

The list of Presenters and Demos is shown below

Demo #AuthorsTitleVideo Link (Optional)
1Dan Pritsker and Colman CheungMonobit Wideband Receiver with Integrated Dithering in FPGA
2Martin Geier, Dominik Faller, Marian Brändle and Samarjit ChakrabortyCombined Energy and Latency Monitoring of a Zynq-based GigE Vision Acquisition/Processing PipelineLink
3Michail Papadimitriou, Juan Fumero, Athanasios Stratikopoulos and Christos KotselidisEnabling Fast Prototyping and Acceleration of Java Programs onto Intel FPGAs with TornadoVM
4Georgi Gaydadjiev and Nils VossPerformance Potability using MaxCompiler
5Jonathan Beaumont, Shane Fleming, Matthew Naylor, David Thomas, Andrew Brown, Andrey Mokhov and Simon MoorePOETS - Partial Ordered Event Triggered Systems
6Haggai Eran, Lior Zeno, Maroun Tork, Gabi Malka, Zsolt István and Mark SilbersteinA SmartNIC-based memcached Accelerator with NICA and ntl
7Daniel Holanda Noronha, Ruizhe Zhao, Jeffrey Goeders, Wayne Luk and Steve WiltonOn-chip FPGA Debug Instrumentation for Machine Learning ApplicationsLink
8Eddie Hung and David ShahYosys+nextpnr: Bet you can't say this tongue twister faster than I can bitstream
9Naif Tarafdar, Varun Sharma and Paul ChowTelepathy: A Multi-FPGA, Multi-CPU Machine Learning Framework Deployed on a Hardware Stack
10Dallon Glick, Jesse Grigg, Brent Nelson and Michael WirthlinMaverick: A Stand-alone CAD Flow for Partially Reconfigurable FPGA Modules
11Richard Chamberlain and Marcus WeddleFPGA Acceleration of Binary Weighted Neural Network InferenceLink
12Dominique Meyer, Akhil Birlangi, Ryan Kastner and Falko KuesterFPGA Accelerated Stereo Depth for Stereo-Panoramic Video and Scene Estimation
13Sergiu Mosanu, Xinfei Guo, Mohamed El-Hadedy, Lorena Anghel and Mircea StanFlexible, Highly-Parameterizable Encryption Modules in Chisel on RISC-V Cores
14Mineto Tsukada, Masaaki Kondo and Hiroki MatsutaniAn FPGA-based On-device Sequential Learning Approach for Unsupervised Anomaly Detection
15Guy LemieuxRunning highly accelerated software on FPGA-based soft and hard processorsLink
16Eugenio Culurciello, Sen Ma and Shanyuan GaoCreating an AI-Generated Portrait via Style Transfer
17Alireza Khodamoradi, Ryan Kastner and Parimal PatelDesigning and Fast Prototyping with PYNQ and Vivado HLS
18John LockwoodReal-time data in connected cities using Key Value Store in FPGA

Tuesday, April 30

Technical Program
Qualcomm Institute Auditorium

TimeSession Title (Chair)Presentation TitleAuthors
8:30Simulation and Infrastructure
(Wei Zhang)
MEG: A RISCV-based system simulation infrastructure for exploring memory optimization using FPGAs and Hybrid Memory CubeJialiang Zhang, Yang Liu, Gaurav Jain, Yue Zha, Jonathan Ta and Jing Li
Enhancing Butterfly Fat Tree NoCs for FPGAs with lightweight flow controlGurshaant Singh Malik and Nachiket Kapre
SimAcc: A Configurable Cycle-Accurate Simulator for customized accelerators on CPU-FPGAs SoCsKonstantinos Iordanou, Oscar Palomar, John Mawer, Cosmin Gorgovan, Andy Nisbet and Mikel Lujan
9:30Morning Break and Poster Session 3: Networking and Resource SharingDetails
10:15Machine Learning 2
(John Lockwood)
Towards Efficient and Scalable Acceleration of Online Decision Tree Learning on FPGAZhe Lin, Sharad Sinha and Wei Zhang
T2S-Tensor : Productively Generating High-Performance Spatial Hardware for Dense Tensor ComputationsNitish Srivastava, Hongbo Rong, Prithayan Barua, Guanyu Feng, Huanqi Cao, Zhiru Zhang, David Albonesi, Vivek Sarkar, Wenguang Chen, Paul Petersen, Geoff Lowney, Adam Herr, Christopher Hughes, Timothy Mattson, Pradeep Dubey
SparseHD: Algorithm-Hardware Co-Optimization for Efficient High-Dimensional ComputingMohsen Imani, Sahand Salamat, Behnam Khaleghi, Mohammad Samragh, Farinaz Koushanfar and Tajana Rosing
Why Compete When You Can Work Together: FPGA-ASIC Integration for Persistent RNNsEriko Nurvitadhi, Dongup Kwon, Ali Jafari, Andrew Boutros, Jaewoong Sim, Phillip Tomson, Huseyin Sumbul, Gregory Chen, Phil Knag, Raghavan Kumar, Ram Krishnamurthy and Debbie Marr
(Ken Eguro)
Design Patterns for Code Reuse in HLS Packet Processing PipelinesHaggai Eran, Lior Zeno, Zsolt István and Mark Silberstein
Module-per-Object: a Human-Driven Methodology for C++-based High-Level Synthesis DesignJeferson Santiago da Silva, François-Raymond Boyer and J.M. Pierre Langlois
Templatised soft floating-point for High-Level SynthesisDavid Thomas
Exploiting Irregular Memory Parallelism In Quasi-Stencils Through Nonlinear TransformationJuan Escobedo and Mingjie Lin
2:10Applications 2
(Roger Moussalli)
FP-AMR: A Reconfigurable Fabric Framework for Adaptive Mesh Refinement ApplicationsTianqi Wang, Tong Geng, Xi Jin and Martin Herbordt
GhostSZ: A Transparent FPGA-Accelerated Lossy Compression FrameworkQingqing Xiong, Chen Yang, Rushi Patel, Geng Tong, Anthony Skjellum and Martin Herbordt
Compressed Sensing MRI Reconstruction on Intel HARPv2 (short)Yushan Su, Michael Anderson, Jonathan Tamir, Michael Lustig and Kai Li
Efficient Hardware Acceleration for Design Diversity Calculation to mitigate Common Mode Failures (short)Maheshwaran Ramesh Babu, Farah Naz Taher, Anjana Balachandran and Benjamin Carrion Schafer
3:00Afternoon Break and Poster Session 4: ApplicationsDetails
3:40Security and Reliability
(Mike Wirthlin)
Fast Voltage Transients on FPGAs: Impact and Mitigation StrategiesLinda L. Shen, Ibrahim Ahmed and Vaughn Betz
FASE: FPGA Acceleration of Secure Function EvaluationSiam Umar Hussain and Farinaz Koushanfar
(James Davis)
Rethinking Integer Divider Design for FPGA-based Soft ProcessorsEric Matthews, Alec Lu, Lesley Shannon and Zhenman Fang
High Precision, High Performance FPGA AddersMartin Langhammer, Bogdan Pasca and Gregg Baeckler
5:05CloseClosing SessionRyan Kastner, André DeHon
5:20End of Technical Program

Poster Session 3: Networking and Resource Sharing

Scalable P4 Deparser for Speeds Over 100GbpsPavel Benacek, Jakub Cabal and Juraj Holub
Wire-Speed Multirate Accelerator for Aggregation Operations on Sorted DataSang-Woo Jun and Arvind
Hybrid XML Parser Based on Software and Hardware Co-designZhe Pan, Xiaohong Jiang, Jian Wu and Xiang Li
Sorting Large Data Sets with FPGA-Accelerated SamplesortHan Chen, Sergey Madaminov, Michael Ferdman and Peter Milder
Cost-effective Energy Monitoring of a Zynq-based Real-time System including dual Gigabit EthernetMartin Geier, Dominik Faller, Marian Brändle and Samarjit Chakraborty
Improved Techniques for Sensing Intra-Device Side Channel LeakageWilliam Hunter, Christopher McCarty and Lee Lerner
Safe Task Interruption for FPGAsSameh Attia and Vaughn Betz

Poster Session 4: Applications

OpenCL Kernel Vectorization on the CPU, GPU, and FPGA:A Case Study with Frequent Pattern CompressionZheming Jin and Hal Finkel
A 4.8x Faster FPGA-Based Iterative Closest Point Accelerator for Object Pose Estimation of Picking Robot ApplicationsAtsutake Kosuge, Keisuke Yamamoto, Yukinori Akamine, Taizo Yamawaki and Takashi Oshima
Monobit Wideband Receiver with Integrated Dithering in FPGADan Pritsker and Colman Cheung
An FPGA-based Computing Infrastructure Tailored to Efficiently Scaffold Genome SequencesAlberto Zeni, Matteo Crespi, Lorenzo Di Tucci and Marco Domenico Santambrogio
FlexGibbs: Reconfigurable Parallel Gibbs Sampling Accelerator for Structured GraphsGlenn Gihyun Ko, Yuji Chai, Rob A. Rutenbar, David Brooks and Gu-Yeon Wei
A Fine-grained Parallel Snappy Decompressor for FPGAs Using a Relaxed Execution ModelJian Fang, Jianyu Chen, Jinho Lee, Zaid Al-Ars and H. Peter Hofstee
Analyzing the Energy-Efficiency of Vision Kernels on Embedded CPU, GPU and FPGA PlatformsMurad Qasaimeh, Joseph Zambreno, Phillip Jones, Kristof Denolf, Jack Lo and Kees Vissers
Large-scale and High-throughput QR Decomposition on an FPGADajung Lee, Andrei Hagiescu and Dan Pritsker
Flexi-AES: A Highly-Parameterizable Cipher for a Wide Range of Design ConstraintsSergiu Mosanu, Xinfei Guo, Mohamed El-Hadedy, Lorena Anghel and Mircea Stan

Wednesday, May 1

Computer Science and Engineering Building

TimeWorkshop Session 1Workshop Session 2  
8:00 Security for Custom Computing Machines
(Dustin Richmond, University of Washington)
Xilinx ML Suite Developer Tutorial ( Parimal Patel, Xilinx)
10:15Security for Custom Computing Machines
Customizing Implementations with RapidWright in the Domain-specific Age (Chris Lavin, Xilinx)
1:15Edge Intelligence and FCCM: ML + IoT +FCCM
(Marilyn Wolf, Georgia Tech)
Intel FPGA New Technology Showcase: Chiplets,
High-Bandwidth Memory, and eASIC
(David Kehlet, Oliver Tan, and Lawrence Landis, Intel Programmable Solutions Group)
5:00Closing RemarksClosing Remarks

Security for Custom Computing Machines

Date: Wednesday May 1, 2019
Time: 8:00 am – 12:15 pm
Location: CSE 1242
Organizers: Dustin Richmond (UW) and Ryan Kastner  (UCSD)

Hardware security is an important design consideration. Recent events have raised awareness of security in general-purpose processors. As experts we must consider: What are equivalent equivalents for custom computing machines? How do we defend against threats that exist today? How do we design our systems to defend against future threats? This is increasingly important as we deploy custom computing machines at unprecedented scales.

Schedule (Preliminary):

8:15Matt French/Josh Monson (ISI)
8:30Dustin Richmond (University of Washington)
Deploying Sensors in the Datacenter
8:45David Kohlbrenner (UC Berkeley)
A Threat Model for Deploying Secure Hardware Elements on Untrusted FPGAs
9:00Jeff Goeders (BYU)
Assurance of Trusted 3rd-Party IP for Modern FPGAs
9:15Christophe Bobda (University of Florida)
System-Level Design of Secure System on Chip
9:30Break-Out Session
10:00Coffee Break
10:30Alric Althoff (Leidos)
Quantifying System-Level Side-Channel Vulnerability
10:45Aydin Aysu (NC State)
Physical Side-Channels Beyond Cryptography: Searching a New Horizon for Hardware Security
11:00Nestan Tsiskaridze (UCSB)
Quantifying Arbitration Side Channels in FPGAs
11:15Ryan Kastner (UCSD)
Security Verification for Heterogeneous Systems
11:30Jonathan Valamehr (Tortuga Logic)
System-Level Security Verification Starts with the Hardware Root of Trust
11:45Break-Out Session

Xilinx ML Suite Developer Tutorial

Date: Wednesday May 1, 2019
Time: 8:00 am- 10:00 am
Location: CSE 3219
Organizer: Parimal Patel – Xilinx Inc.

With the explosion of large amount of unstructured data generated at various levels, from endpoints to edge to cloud, quick and accurate information processing has driven researchers to consider ways to analyze the data and act on it in real-time. Xilinx’s new Machine Learning Suite enables users to easily evaluate, develop and deploy FPGA-accelerated ML inference using ready-to-run network models so that they can easily integrate machine learning into their research. This tutorial uses the Xilinx ML Suite to deploy models for real-time inference on Amazon EC2 F1 FPGA instances. During this lab you will use Python APIs to accelerate your ML applications with Amazon EC2 F1 instances powered by Xilinx FPGAs. It will provide users an experience on evaluating image classification through Caffe, MxNet and Tensorflow.

Please Note: Attendees will use their laptop to connect to AWS

Customizing Implementations with RapidWright
in the Domain-specific Age

Date: Wednesday May 1, 2019
Time: 10:15 am- 12:15 pm
Location: CSE 3219
Organizer/Speaker: Chris Lavin – Xilinx Inc.

As we enter a new Golden Age of computer architecture, we need new capabilities to build and customize domain-specific applications for FPGAs.  RapidWright is an open source framework that provides a gateway to Vivado’s back-end tools enabling fine-grained control over implementation.  This workshop provides hands-on experience and live coding with RapidWright to illustrate its capabilities such as:

  • Implementation “copy and paste” to create a ~400 instance PicoBlaze overlay
  • Using a SAT engine to resolve difficult routing congestion
  • Combine a RapidWright-generated SLR bridge with Vivado-based designs

Attendees of this workshop can expect to: (1) gain a deeper understanding of how to leverage Xilinx architecture, (2) know how to use RapidWright and apply its capabilities in their own designs and (3) learn about design methodologies that can lead to near-spec performance.

Please Note: Attendees will use their laptop to connect to AWS

Edge Intelligence and FCCM: ML + IoT +FCCM

Date: Wednesday May 1, 2019
Time: 1:15 pm- 5:00 pm
Location: CSE 1242
Organizer: Marilyn Wolf (Georgia Tech)

This workshop will focus on the emerging intersections between machine learning, IoT, and field-programmable custom computing. Machine learning offers broad applicability to a wide range of applications: manufacturing, agriculture, logistics, health care, smart cities, etc. However, in physically distributed and real-time applications for which IoT architectures are used, machine learning systems cannot be limited to the cloud. The need for low-power, managed-latency, distributed machine learning in turn presents significant opportunities for the application of field-programmable computing. The workshop combines a set of  invited talks with contributed presentations.

Intel FPGA New Technology Showcase: Chiplets,
High-Bandwidth Memory, and eASIC

Date: Wednesday May 1, 2019
Time: 1:15- 5:00 pm
Location: CSE 3219
Organizers: David Kehlet, Oliver Tan, and Lawrence Landis
Intel Programmable Solutions Group

Today’s markets are rapidly transforming which is driving massive innovation and putting great demand on capabilities that provide the agility and flexibility to quickly and cost effectively deliver products and solutions. In this workshop, Intel will provide insights into new and unique capabilities that enable engineers, researchers, and innovators to deliver high-performance solutions to drive massive disruption and opportunity.

This workshop include three talks: The first talk is on standardized chiplet interfaces, which are critical for enabling heterogenous compute in package and inter-operability. The second talk is on in-package highbandwidth memory, which is the key to unlocking near-memory computing for emerging applications. The third talk presents a seamless transition from FPGAs to lower power high performance structured ASICs, which opens up new opportunities for the FPGA community.