Alon Amid

Berkeley College — United States

Computer Science · Physical Sciences

10h-index1.4kcitations24works0.02yr avg
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Research Topics

Parallel Computing and Optimization Techniques(10), Advanced Memory and Neural Computing(6), Advanced Neural Network Applications(5), Embedded Systems Design Techniques(5), CCD and CMOS Imaging Sensors(5)

Publications24 total

Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via Full-Stack Integration
2021· 16 citedOpen Access
A 16mm<sup>2</sup> 106.1 GOPS/W Heterogeneous RISC-V Multi-Core Multi-Accelerator SoC in Low-Power 22nm FinFET
2021· 21 cited
Table of Contents
IEEE Micro·2021Open Access
Accessible, FPGA Resource-Optimized Simulation of Multiclock Systems in FireSim
IEEE Micro·2021· 4 cited
Vertically Integrated Computing Labs Using Open-Source Hardware Generators and Cloud-Hosted FPGAs
2021· 7 cited
FireMarshal: Making HW/SW Co-Design Reproducible and Reliable
2021· 7 cited
COBRA: A Framework for Evaluating Compositions of Hardware Branch Predictors
2021· 2 cited
Invited: Chipyard - An Integrated SoC Research and Implementation Environment
2020· 12 cited
Chipyard: Integrated Design, Simulation, and Implementation Framework for Custom SoCs
IEEE Micro·2020· 318 cited
FirePerf
2020· 15 citedOpen Access
Programmable Fine-Grained Power Management and System Analysis of RISC-V Vector Processors in 28-nm FD-SOI
IEEE Solid-State Circuits Letters·2020· 5 cited
Gemmini: An Agile Systolic Array Generator Enabling Systematic Evaluations of Deep-Learning Architectures
arXiv (Cornell University)·2019· 52 citedOpen Access
Gemmini: Enabling Systematic Deep-Learning Architecture Evaluation via\n Full-Stack Integration
arXiv (Cornell University)·2019· 3 citedOpen Access
Co-design of deep neural nets and neural net accelerators for embedded vision applications
IBM Journal of Research and Development·2019· 5 cited
FireSim: FPGA-Accelerated Cycle-Exact Scale-Out System Simulation in the Public Cloud
IEEE Micro·2019· 7 cited
Co-design of deep neural nets and neural net accelerators for embedded vision applications
2018· 25 cited
Invited: Co-Design of Deep Neural Nets and Neural Net Accelerators for Embedded Vision Applications
2018 55th ACM/ESDA/IEEE Design Automation Conference (DAC)·2018· 8 cited
FireSim: FPGA-Accelerated Cycle-Exact Scale-Out System Simulation in the Public Cloud
2018· 212 cited
Co-Design of Deep Neural Nets and Neural Net Accelerators for Embedded Vision Applications
arXiv (Cornell University)·2018· 7 citedOpen Access
Co-Design of Deep Neural Nets and Neural Net Accelerators for Embedded\n Vision Applications
arXiv (Cornell University)·2018Open Access
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Frequent Co-authors

Krste Asanović(19), Borivoje Nikolić(13), Howard Mao(9), Colin Schmidt(9), Sagar Karandikar(8), Albert Ou(8), Jerry Zhao(8), David Biancolin(6), John Wright(6), Yakun Sophia Shao(6), Nathan Pemberton(5), Jonathan Bachrach(5), BoRui Wu(5), Kurt Keutzer(5), Abraham Gonzalez(4), Harrison Liew(4), Albert Magyar(4), Kiseok Kwon(4), Daniel Grubb(3), Randy H. Katz(3)