Ahmet Alper Goksoy
Graduate Research Assistant at University of Wisconsin-Madison
Graduate Research Assistant at University of Wisconsin-Madison
Domain Specific SoCs, Task Scheduling, Graph Neural Networks, Reinforcement Learning
University of Wisconsin-Madison
https://www.linkedin.com/company/uwmadison
Graduate Research Assistant
- Developed a zero-overhead, energy-efficient task scheduling (DAS) framework that combines benefits of a fast, low-overhead scheduler and a high-performance, high-overhead scheduler for heterogeneous SoCs.
- Performed a detailed theoretical analysis of DAS framework and its validation on a system level simulator.
- Developed Graph Neural Network (GNN) and Deep Neural Network (DNN) based Imitation Learning (IL) and Reinforcement Learning (RL) task schedulers for domain-specific SoCs.
- Contributed to an in-memory computing-based GNN hardware accelerator design.
- Developing sparsity eliminator algorithms for a communication-aware GNN hardware accelerator design. 
- Developing hardware-aware neural architecture search (NAS) algorithms for sparse neural networks.
- Contributed to the development of a system-level domain-specific SoC simulation framework.
Madison, Wisconsin, United States
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Arizona State University
https://www.linkedin.com/company/arizona-state-university
Graduate Research Assistant
- Contributed to the development of an IL-based task scheduling framework for heterogeneous SoCs.
- Contributed to the development of a system-level domain-specific SoC simulation framework.
Phoenix, Arizona Area
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Mikroelektronik Ltd. (MKR-IC)
https://www.linkedin.com/company/mikroelektronik-ltd-
Intern
Designed a single-ended 8 bit 250 MSPS SAR ADC.
Istanbul, Turkey
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Aselsan
https://www.linkedin.com/company/aselsan
Intern
Contributed to the development of RTOS for an SoC board using VxWorks.
Ankara, Turkey
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Arcelik Group
https://www.linkedin.com/company/arcelikglobal
R&D Software Applications Intern
Designing test programs for the production line and fixing bugs on TVs. Designing test programs for experiments to decrease the time of the White Colour Balance Process.
İstanbul, Türkiye
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BUEC - Boğaziçi IEEE Student Branch
https://www.linkedin.com/company/buec---bo%C4%9Fazi%C3%A7i-ieee-student-branch
Member
İstanbul, Türkiye
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Electrical Engineering
Doctor of Philosophy - PhD
University of Wisconsin-Madison
https://www.linkedin.com/school/uwmadison/
Transferred from ASU
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Electrical Engineering
Doctor of Philosophy - PhD
Arizona State University
https://www.linkedin.com/school/arizona-state-university/
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Electrical and Electronics Engineering
Bachelor's degree
Boğaziçi University
https://www.linkedin.com/school/bogazici-university/
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Sociology
Bachelor of Arts - BA
Istanbul University
https://www.linkedin.com/school/istanbul-university/
Online Education Program
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Isparta Süleyman Demirel Fen Lisesi
DAS: Dynamic Adaptive Scheduling for Energy-Efficient Heterogeneous SoCs
IEEE
Domain-specific systems-on-chip (DSSoCs) aim at bridging the gap between application-specific integrated circuits (ASICs) and general-purpose processors. Traditional operating system (OS) schedulers can undermine the potential of DSSoCs since their execution times can be orders of magnitude larger than the execution time of the task itself. To address this problem, we propose a dynamic adaptive scheduling (DAS) framework that combines the benefits of a fast (low-overhead) scheduler and a slow (sophisticated, high-performance but high-overhead) scheduler. Experiments with five real-world streaming applications show that DAS consistently outperforms both the fast and slow schedulers. For 40 different workloads, DAS achieves on average 1.29× speedup and 45% lower EDP compared to the sophisticated scheduler at low data rates and 1.28× speedup and 37% lower EDP than the fast scheduler when the workload complexity increases
https://ieeexplore.ieee.org/iel7/4563995/5170179/09530260.pdf
Runtime task scheduling using imitation learning for heterogeneous many-core systems
IEEE
Domain-specific systems-on-chip, a class of heterogeneous many-core systems, are recognized as a key
approach to narrow down the performance and energy-efficiency gap between custom hardware accelerators and programmable processors. Reaching the full potential of these architectures
depends critically on optimally scheduling the applications to available resources at runtime. Existing optimization-based techniques cannot achieve this objective at runtime due to the combinatorial nature of the task scheduling problem. As the main theoretical contribution, this paper poses scheduling
as a classification problem and proposes a hierarchical imitation learning (IL)-based scheduler that learns from an Oracle to maximize the performance of multiple domain-specific applications. Extensive evaluations with six streaming applications from wireless communications and radar domains
show that the proposed IL-based scheduler approximates an offline Oracle policy with more than 99% accuracy for performance- and energy-based optimization objectives.  Furthermore, it achieves almost identical performance to the Oracle with a low runtime overhead and successfully adapts to
new applications, many-core system configurations, and runtime variations in application characteristics
https://arxiv.org/pdf/2007.09361.pdf
DS3: A System-Level Domain-Specific System-on-Chip Simulation Framework
IEEE
Heterogeneous systems-on-chip (SoCs) are highly favorable computing platforms due to their superior performance and energy efficiency potential compared to homogeneous architectures. They can be further tailored to a specific domain of applications by incorporating processing elements (PEs) that accelerate frequently used kernels in these applications. However, this potential is contingent upon optimizing the SoC for the target domain and utilizing its resources effectively at runtime. To this end, system-level design - including scheduling, power-thermal management algorithms, and design space exploration studies - plays a crucial role. This article presents a system-level domain-specific SoC simulation (DS3) framework to address this need. DS3 enables both design space exploration and dynamic resource management for power-performance optimization of domain applications. We showcase DS3 using six real-world applications from wireless communications and radar processing domain. DS3, as well as the reference applications, is shared as open-source software to stimulate research in this area
https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9072509
A simulation framework for domain-specific system-on-chips: work-in-progress
ACM
https://dl.acm.org/doi/pdf/10.1145/3349567.3351719
DAC 2021 Young Fellowship
Design Automation Conference (DAC)
I received a full free registration to DAC 2021 and worked on a hands-on lab experience where we designed a NN accelerator using a High Level Synthesis tool.
Richard Newton Young Fellow
Design Automation Conference (DAC)
I received a full free DAC (Design Automation Conference) registration, along with a travel award that covers travel, lodging, and incidentals.
Advanced Computer Architecture I
ECE 752
CAD Tools in VLSI
CS 756
Introduction to Computer Architecture
ECE 552
Computational Image Understanding and Pattern Analysis
EEE 598
Minds and Machines
AME 598
Reinforcement Learning
CSE 691
Statistical Machine Learning
EEE 598
System Level Design for Multicore Architectures
EEE 598
VLSI Design
EEE 525
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High Level Synthesis Tutorial - DAC 2021
www.credly.com
Cadence Design Systems
https://tr.linkedin.com/in/g%C3%B6n%C3%BCl-%C5%9Fakar-082542162
Gönül Şakar
Software Engineer at Turkish Aerospace
Turkey
https://tr.linkedin.com/in/gokcan-tatli-298380a0
Gokcan Tatli
PhD Student at UW-Madison
Istanbul
https://www.linkedin.com/in/safamedin
Safa C. Medin
Graduate Research Assistant at Massachusetts Institute of Technology
Cambridge, MA
https://ch.linkedin.com/in/ozan-yakar-85077a112
Ozan Yakar
Doctoral Student at EPFL (École polytechnique fédérale de Lausanne)
Lausanne Metropolitan Area
https://tr.linkedin.com/in/%C3%A7a%C4%9Fatay-ate%C5%9F-484439134
Çağatay Ateş
Boğaziçi Üniversitesi şirketinde Research Assistant
Besiktas
https://tr.linkedin.com/in/iremsireli
İrem Şireli
Software Developer at IOTIQ GmbH
Ankara, Turkey
https://tr.linkedin.com/in/ismail-rasim-%C3%BClgen-8566789b
İsmail Rasim Ülgen
R&D Engineer at Sestek
Turkey
https://de.linkedin.com/in/deniz-tomar-603441134
Deniz Tomar
Graduate Student at Technical University of Munich | Communications Engineering
Munich
https://fr.linkedin.com/in/%C3%A7a%C4%9Fla-okyay-5180591ba
Çağla Okyay
PhD Candidate in Physics at Université Paris-Saclay
Évry
https://www.linkedin.com/in/bengisucagiltay
Bengisu Cagiltay
Graduate Research Assistant at University of Wisconsin-Madison
Madison, WI
https://www.linkedin.com/in/u%C4%9Fur-cin-1114a020a
Uğur Cin
Ph.D. Student in Mathematics
Madison, WI
https://tr.linkedin.com/in/umut-mi%C5%9Fe-b78030202
Umut Mişe
PhD Candidate - Boğaziçi Üniversitesi
Istanbul, Turkey
https://www.linkedin.com/in/sri-subramanian
Srinath Subramanian
Graduate Research Assistant at University of Wisconsin-Madison
Madison, WI
https://www.linkedin.com/in/tuo-wang-0485b5133
Tuo Wang
Ph.D. Student in UW-Madison
Madison, WI
https://www.linkedin.com/in/kgodeneli
Kadircan Gödeneli
PhD Student at UC Berkeley
Berkeley, CA
https://tr.linkedin.com/in/burak-sefa-sert-4b1787105
Burak Sefa SERT
--
Ankara, Turkey
https://www.linkedin.com/in/dogadogan
Mustafa Doga Dogan
PhD Candidate at MIT Computer Science and Artificial Intelligence Laboratory (CSAIL)
Greater Boston
https://www.linkedin.com/in/mostafaessawy
Mostafa Essawy
Doctoral Student at Oregon State University
Corvallis, OR
https://www.linkedin.com/in/pooja-guhan
Pooja Guhan
CS PhD student @ UMD | vGHC'21 | Adobe Research Intern 2021
College Park, MD
https://www.linkedin.com/in/gajanan-kothawade-b94b8291
Gajanan Kothawade
Graduate Research Assistant | Center for Precision and Automated Agricultural Systems | Dept of Biological Systems Engineering | Washington State University
Prosser, WA
Congratulations to Associate Professor Umit Ogras for being named Outstanding Researcher by Intel!Read the full…
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Just presented our work "Control Variate Approximation for DNN Accelerators", a collaboration with the Karlsruhe Institute of Technology and the…
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ECE Associate Professor Umit Ogras and PhD student Sumit Kumar Mandal received the 2021 best paper award from the ACM, Association for Computing…
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Hire a Badger Engineer
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Boğaziçi University Students
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BUEC - Boğaziçi IEEE Alumni Network
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