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Daniel Grubb

dblp:271/3260 · DBLP profile ↗
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3ranked-venue papers
0as first author
2since 2021 · last 2022
0000-0002-3510-6169ORCID · corroborated

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

Systems, architecture and hardware · 3 · 2 since 2021

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
3 papers
Electronic design automation · 55% Hardware accelerators and domain-specific architectures · 17% Integrated circuit design · 17%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Electronic design automation
design space exploration
0.612022
Hammer: a modular and reusable physical design flow tool: invited · DAC 2022
Electronic design automation
physical design
0.612022
Hammer: a modular and reusable physical design flow tool: invited · DAC 2022
Hardware accelerators and domain-specific architectures › machine learning accelerator
DNN accelerator
0.512021
Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration · DAC 2021
Integrated circuit design › system-on-chip
system-on-chip integration
0.512021
Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration · DAC 2021
Electronic design automation › system-level design › system design methodology
system-on-chip design flow
0.412020
Invited: Chipyard - An Integrated SoC Research and Implementation Environment · DAC 2020
Processor architecture and microarchitecture › instruction set architecture › RISC-V
RISC-V core design
0.212022
Hammer: a modular and reusable physical design flow tool: invited · DAC 2022
Reconfigurable computing and FPGAs
FPGA prototyping
0.112020
Invited: Chipyard - An Integrated SoC Research and Implementation Environment · DAC 2020

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

modular software architecture · 0.6flow step generators · 0.6generator-based design · 0.4agile hardware design · 0.4
YearPublicationVenuePosition
2022 Hammer: a modular and reusable physical design flow tool: invited
abstract
Process technology scaling and hardware architecture specialization have vastly increased the need for chip design space exploration, while optimizing for power, performance, and area. Hammer is an open-source, reusable physical design (PD) flow generator that reduces design effort and increases portability by enforcing a separation among design-, tool-, and process technology-specific concerns with a modular software architecture. In this work, we outline Hammer's structure and highlight recent extensions that support both physical chip designers and hardware architects evaluating the merit and feasibility of their proposed designs. This is accomplished through the integration of more tools and process technologies---some open-source---and the designer-driven development of flow step generators. An evaluation of chip designs in process technologies ranging from 130nm down to 12nm across a series of RISC-V-based chips shows how Hammer-generated flows are reusable and enable efficient optimization for diverse applications.
Harrison Liew, Daniel Grubb, Colin Schmidt 0001, Nayiri Krzysztofowicz, Adam M. Izraelevitz, Krste Asanovic, Jonathan Bachrach, Borivoje Nikolic
DAC2
2021 Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration
abstract
DNN accelerators are often developed and evaluated in isolation without considering the cross-stack, system-level effects in real-world environments. This makes it difficult to appreciate the impact of Systemon-Chip (SoC) resource contention, OS overheads, and programming-stack inefficiencies on overall performance/energy-efficiency. To address this challenge, we present Gemmini, an open-source, full-stack DNN accelerator generator. Gemmini generates a wide design-space of efficient ASIC accelerators from a flexible architectural template, together with flexible programming stacks and full SoCs with shared resources that capture system-level effects. Gemmini-generated accelerators have also been fabricated, delivering up to three orders-of-magnitude speedups over high-performance CPUs on various DNN benchmarks.
Hasan Genc, Seah Kim, Alon Amid, Ameer Haj-Ali, Vighnesh Iyer, Pranav Prakash, Jerry Zhao, Daniel Grubb, Harrison Liew, Howard Mao, Albert J. Ou, Colin Schmidt 0001, Samuel Steffl, John Charles Wright, Ion Stoica, Jonathan Ragan-Kelley, Krste Asanovic, Borivoje Nikolic, Sophia Shao
DAC8
2020 Invited: Chipyard - An Integrated SoC Research and Implementation Environment
abstract
Continued improvement in computing efficiency requires functional specialization of hardware designs. We present an agile design flow for custom SoCs using the Chipyard framework, an integrated SoC research and implementation environment for custom systems. Chipyard includes configurable, composable, open-source, generator-based designs that can be used across multiple stages of the hardware development flow while maintaining design intent and integration consistency. Through cloud FPGA simulation and rapid ASIC implementation, we demonstrate an iterative agile hardware design cycle which enables continuous validation of physically-realizable customized systems.
Alon Amid, David Biancolin, Abraham Gonzalez, Daniel Grubb, Sagar Karandikar, Harrison Liew, Albert Magyar, Howard Mao, Albert J. Ou, Nathan Pemberton, Paul Rigge, Colin Schmidt 0001, John Charles Wright, Jerry Zhao, Jonathan Bachrach, Sophia Shao, Borivoje Nikolic, Krste Asanovic
DAC4