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Trevor Bauer

dblp:158/8237 · DBLP profile ↗
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4ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 4

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
2 papers
Reconfigurable computing and FPGAs · 95% Electronic design automation · 5%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Reconfigurable computing and FPGAs
FPGA architecture
0.622019
Xilinx Adaptive Compute Acceleration Platform: VersalTM Architecture · FPGA 2019
Enhancements in UltraScale CLB Architecture · FPGA 2015
Reconfigurable computing and FPGAs › reconfigurable architecture
adaptive compute acceleration platform
0.412019
Xilinx Adaptive Compute Acceleration Platform: VersalTM Architecture · FPGA 2019
Reconfigurable computing and FPGAs › FPGA architecture
configurable logic block
0.212015
Enhancements in UltraScale CLB Architecture · FPGA 2015
Electronic design automation
physical design
0.112015
Enhancements in UltraScale CLB Architecture · FPGA 2015

Methods — techniques the papers use, named apart from their topics

architecture evaluation · 0.2
YearPublicationVenuePosition
2020 Xilinx Versal™ Premium
abstract
This article consists only of a collection of slides from the author's conference presentation.
Martin Voogel, Yohan Frans, Matt Ouellette, Jason Coppens, Sagheer Ahmad, Jaideep Dastidar, Ehab Mohsen, Faisal Dada, Mike Thompson, Ralph Wittig, Trevor Bauer
Hot Chips Symposium11
2019 Xilinx Adaptive Compute Acceleration Platform: VersalTM Architecture
abstract
In this paper we describe Xilinx's Versal-Adaptive Compute Acceleration Platform (ACAP). ACAP is a hybrid compute platform that tightly integrates traditional FPGA programmable fabric, software programmable processors and software programmable accelerator engines. ACAP improves over the programmability of traditional reconfigurable platforms by introducing newer compute models in the form of software programmable accelerators and by separating out the data movement architecture from the compute architecture. The Versal architecture includes a host of new capabilities, including a chip-pervasive programmable Network-on-Chip (NoC), Imux Registers, compute shell, more advanced SSIT, adaptive deskew of global clocks, faster configuration, and other new programmable elements as well as enhancements to the CLB and interconnect. We discuss these architectural developments and highlight their key motivations and differences in relation to traditional FPGA architectures.
Brian Gaide, Dinesh Gaitonde, Chirag Ravishankar, Trevor Bauer
FPGA4
2018 Placement Strategies for 2.5D FPGA Fabric Architectures
abstract
FPGAs take advantage of 2.5D stacking technology to manufacture large capacity and high performance heterogeneous devices at reasonable costs. EDA tools need to be aware of and exploit physical characteristics of such devices, for example the reduced connection count between SLRs, the infrequency of SLL channel occurence in the fabric, and the aspect ratios of individual SLRs. We implement a partition driven placer to explore various EDA options to take advantage of architectural features in 2.5D FPGAs. We improve the routability of designs by optimizing the placer for discrete SLL channels and reduced connection counts. We propose a cut schedule for the partitioner to orient the placement with awareness of the aspect ratio of SLRs to improve track demands within each SLR.
Chirag Ravishankar, Dinesh Gaitonde, Trevor Bauer
FPL3
2015 Enhancements in UltraScale CLB Architecture
abstract
Each generation of FPGA architecture benefits from optimizations around its technology node and target usage. In this paper, we discuss some of the changes made to the CLB for Xilinx's 20nm UltraScale product family. We motivate those changes and demonstrate better results than previous CLB architectures on a variety of metrics. We show that, in demanding scenarios, logic placed in an UltraScale device requires 16% less wirelength than 7-series. Designs mapped to UltraScale devices also require fewer logic tiles. In this paper, we demonstrate the utilization benefits of the UltraScale CLB attributed to certain CLB enhancements. The enhancements described herein result in an average packing improvement of 3% for the example design suite. We also show that the UltraScale architecture handles aggressive, tighter packing more gracefully than previous generations of FPGA. These significant reductions in wirelength and CLB counts translate directly into power, performance and ease-of-use benefits.
Shant Chandrakar, Dinesh Gaitonde, Trevor Bauer
FPGA3