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I am an assistant professor of Computer Science and Electrical and Computer Engineering at Duke University. 

My research focuses on how to unleash the unprecedented computational power and efficiency of hardware acceleration to expedite and advance research in areas related to big data, natural science, and healthcare to improve human flourishing — specifically, leveraging the insights derived from a deep understanding of applications (e.g., data structures, data access patterns, computational patterns, application characteristics) to create innovative hardware and software systems to tackle impactful problems. In addition, I am improving the ecosystem for architects to develop and deploy accelerators more easily and for non-hardware users to take advantage of the efficient accelerated systems with a low barrier to entry.

I enjoy solving challenging problems related to computer architecture and microarchitecture, hardware-software co-designs, hardware specialization, accelerators, and architecting accelerated systems in emerging application domains such as big data analytics (e.g., genomic analytics, graph analytics, and database analytics), natural language processing for protein discovery, and computer vision for physiotherapy and rehabilitation. One of my research goals is to greatly simplify the design, deployment, and usage of custom hardware (e.g., AI-assisted synthesis prediction) and to leverage this research in hardware acceleration to advance state-of-the-art research in the healthcare domain as well as other natural sciences. 

Recent News

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IISWC 2024 will be held on Sept 15-17 in Vancouver, British Columbia. Join Omesh Tickoo and me (the PC Co-Chairs) for a great conference!

2024 IEEE International Symposium on Workload Characterization is dedicated to the understanding and characterization of workloads that run on all types of computing systems. Check out the conference program here!

Sep 2024
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APEX Lab welcomes graduate researcher Ning Liang! Ning is a first year CS PhD student at Duke.

Ning has a B.S. and an M.S. from the University of Michigan. His research interests are in computer architecture and database systems.

Aug 2024
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Selected for VMWare Early Faculty Grant Award as part of the 2023 cohort!

The VMWare Early Career Faculty Grant program is intended to recognize the next generation of exceptional faculty members. A gift to the researcher’s university is made in support of his/her research and to promote excellence in teaching. 

Nov 2023
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Our paper "Fast, Robust and Transferable Prediction for Hardware Logic Synthesis" will be presented at MICRO in Toronto.

Entropy Xu will tell you about SNSv2, a transferable synthesis predictor that can be trained on one technology node and predict the physical characteristics of arbitrary circuit designs for other technology nodes without retraining.

Oct 2023
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Our paper "PyTFHE: An End-to-End Compilation and Execution Framework for Fully Homomorphic Encryption Applications" won the ISPASS Best Paper Award in Raleigh!

Mason Ma will tell you about PyTFHE, a highly productive end-to-end framework for FHE application development. PyTFHE achieves orders of magnitude more efficient FHE application execution compared to other SOTA frameworks.

Apr 2023
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APEX Lab welcomes graduate researcher Pragya Sharma! Pragya is a first year ECE PhD student at Duke.

Pragya has a B.S. and an M.S. from Mercer University. Her research interests are in AI and computer vision.

Nov 2022
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APEX Lab welcomes graduate researcher Mansi Choudhary! Mansi is a first year ECE PhD student at Duke.

Mansi has a B.S. and an M.S. from IIT Madras. Her research interests are in computer architecture and accelerating LLMs.

Aug 2022
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Our paper "SNS’s not a Synthesizer: A Deep-Learning-Based Synthesis Predictor" will be presented at ISCA in NYC! This work is selected as an IEEE MICRO Top Pick Honorable Mention.

Entropy Xu will tell you how to predict the area, power, and timing physical characteristics of a broad range of designs at two to three orders of magnitude faster than the Synopsys Design Compiler!

Jun 2022
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APEX Lab welcomes graduate researcher Chris Kjellqvist! Chris will be a third year CS PhD student at Duke.

Chris has a B.S. from the University of Rochester. His research interests are in programming languages, architecture, accelerator development frameworks,  and compilers.

May 2022
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Our paper "ProSE: The Architecture and Design of a Protein Discovery Engine" will be presented at ASPLOS in Lausanne!

Eyes Robson and Entropy Xu will tell you how to increase the power efficiency of predicting drug targets by one to two orders of magnitude compared to an A100 GPU. Come by our poster!

Feb 2022
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APEX Lab welcomes its third graduate researcher Mason Ma! Mason is a first year CS PhD student at Duke.

Mason has a B.S. from UC Irvine. His research interests are in homomorphic encryption, hardware specialization, and computer architecture.

Jan 2022
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NSF awarded the Duke-led Athena AI Institute to transform the design, operation, and services of future mobile devices and networked systems!

Our team is specifically focused on exploring innovations related to AI-powered computer systems at the edge.

Oct 2021
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APEX is now part of the ADA (Applications Driving Architectures) Center, focusing on democratizing the design and manufacturing of next-generation computing systems.

Our team is specifically focused on exploring innovations related to Algorithm-Driven Architectures.

Aug 2021
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"Effectuating Hardware-Accelerated Systems with Domain-Specific Primitives" is selected for the NSF Faculty Early Career Development Program (CAREER) Award!

The CAREER Program is a Foundation-wide activity that offers the National Science Foundation's most prestigious awards in support of early-career faculty.

Dec 2020
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Selected for the Google "Rising" Systems Faculty Award!

Google SysInfra recognizes and supports the next stage of rising scholars' careers in research, teaching, and mentoring. Collectively, the 7 awardees represent 14+ universities in their advanced studies and faculty positions. Thank you Google!!

Oct 2020
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APEX Lab welcomes its second graduate researcher Entropy Xu! Entropy is a first year CS PhD student at Duke.

Entropy has a B.S. from UC Irvine. His research interests are in microarchitecture, hardware agile development, stochastic computing, and accelerator architecture.

Sep 2020
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CS/ECE Undergraduate Course:
Computer Architecture

Checkout the Fall 2020 CS/ECE 250 Course Website!

Aug 2020
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Our paper at ISCA 2020 showcases a project that accelerates the genomic secondary analysis pipeline (part of GATK4) using a framework called Genesis. This work has been selected as an IEEE MICRO Top Pick and an ISCA@50 Retrospective.

Genesis is a framework for accelerating genomic data manipulation operations. Genesis has a SQL-esque frontend and a hardware library of composable components.

Jun 2020
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Selected for the Systems for ML Facebook Research AwardProject: "Accelerating and Deploying Natural Language Processing Systems in Data Centers"

Along with Isaac Robson, a master's student at UNC, we will explore how accelerated NLP systems can help with drug discovery and more.

Feb 2020
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APEX Lab welcomes its first graduate researcher Phyllis Ang!
Phyllis is a first year CS PhD student at Duke.

Phyllis is from Houston, TX and she has a B.S. from UT Austin. Her research interests are in computer architecture, AI, and systems.

Nov 2019
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Chisel Bootcamp Sponsored by APEX Lab @ Duke:
Open to Students and Industry Hardware Architects

Check out the Chisel Bootcamp hosted at Duke on Friday, September 6!

Register for the event here! Space is limited.

Sep 2019
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New CS/ECE Graduate Course:
Computer Architecture and Hardware Acceleration

Check out the Fall 2019 CS/ECE 590 course website!

Fall 2019
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Started a New Lab:
APEX Lab @ Duke (Application-driven Programmable Efficient Accelerated Systems Lab)
Summer 2019
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Awarded Clare Boothe Luce Assistant Professorship

The CBL Program @ The Henry Luce Foundation

Summer 2019
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