Faculty

Institution

Unit

Venue

Dean Tullsen

Professor

University of California, San Diego

Affiliations

Jacobs School of Engineering

Computer Science & Engineering

Dean Tullsen is currently serving as a Computer Science & Engineering Professor at University of California, San Diego.

Honors

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Experiences

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Education

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Dean Tullsen

University of California, San Diego

Professor

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computer science computer engineering parallel computing computer architecture high performance computer architecture microarchitecture systems engineering machine learning processor architectures electrical engineering many-core architectures manycore processor computer security multithreading (computer architecture) energy efficiency hardware security scalability distributed systems heterogeneous computing multiprocessor systems distributed computing data security high-performance architectures power-aware computing side-channel attacks scheduling (computing) energy management power-efficient computing hardware acceleration thermal management simultaneous multithreading parallel programming thermal engineering compiler technology software security computational intelligence computational optimization software analysis communication security power electronics design automation distributed processing hardware architecture instruction-level parallelism concurrent systems concurrency (computer science) power management multi-core architectures engineering optimization computer-aided design field programmable gate array interconnection network architecture power-aware design data center management memory management dynamic optimization gpu computing high performance computing adversarial machine learning runtime systems concurrent programming symbiotic jobscheduling heterogeneous chip multiprocessors processor power dissipation power requirements thread-level parallelism speculative precomputation single chip simultaneous multithreading processor context-sensitive fencing isa diversity single isa speculative leaks cryptographic code redundant computation decision science system software

Notable Scholarly Works

Notable Federal Grants

Collaborators

Hardware-Assisted Fault Isolation: Going Beyond the Limits of Software-Based Sandboxing. IEEE Micro (2024)

Shravan NarayanTal GarfinkelMohammadkazem TaramJoey RudekDaniel MoghimiEvan JohnsonChris FallinAnjo Vahldiek-OberwagnerMichael LeMayRavi SahitaDean TullsenDeian Stefan

systems engineeringmicro-electromechanical systemsengineeringmicro technologyelectrical engineeringflexible electronicshardware security

PATHFINDER: High-Resolution Control-Flow Attacks Exploiting the Conditional Branch Predictor. International Conference on Architectural Support for Programming Languages and Operating Systems (2024)

Hosein YavarzadehArchit AgarwalMax ChristmanChristina GarmanDaniel GenkinAndrew KwongDaniel MoghimiDeian StefanKazem TaramDean Tullsen

computer sciencehigh-resolution control-flow attackscomputer securityconditional branch predictormachine learning

PDIP: Priority Directed Instruction Prefetching. International Conference on Architectural Support for Programming Languages and Operating Systems (2024)

Bhargav Reddy GodalaSankara Prasad RameshGilles A. PokamJared StarkAndre SeznecDean TullsenDavid I. August

computer scienceinstruction prefetchingparallel computingoperating systemsscheduling (computing)

Half Half: Demystifying Intel’s Directional Branch Predictors for Fast, Secure Partitioned Execution. 2022 IEEE Symposium on Security and Privacy (SP) (2023)

Hosein YavarzadehMohammadkazem TaramShravan NarayanDeian StefanDean Tullsen

computer sciencedeep learningcomputer securitydirectional branch predictorsdemystifying intelmachine learning

EVAX: Towards a Practical, Pro-Active Adaptive Architecture for High Performance Security. IEEE/ACM International Symposium on Microarchitecture (2022)

Samira Mirbagher AjorpazDaniel MoghimiJeffrey Neal CollinsGilles PokamNael Abu-GhazalehDean Tullsen

systems engineeringhigh performanceadaptive architecturearchitecturecomputer securityhigh-performance architectures

Mitigating Speculative Execution Attacks via Context-Sensitive Fencing. IEEE Design and Test (2022)

Mohammadkazem TaramAshish VenkatDean Tullsen

computer sciencecontext-sensitive fencingsoftware analysistargeted attackspeculative execution attacksinformation securitycomputer engineeringcomputer securitydata securitymicrocode-level defensehardware securityoperating systemsside-channel attacks

AGON: A Scalable Competitive Scheduler for Large Heterogeneous Systems. arXiv (Cornell University) (2021)

Andreas ProdromouAshish VenkatDean M. Tullsen

artificial intelligencecomputer sciencehigh performance computer architecturescalabilitycompetitive scheduling approachperformance predictionheterogeneous computingscalable competitive schedulercomputer engineeringparallel computingneural network (machine learning)computer architectureneural network-based classifiercluster computingscheduling (computing)scheduling problemsmachine learning

Automatically Eliminating Speculative Leaks From Cryptographic Code With Blade. Proceedings of the ACM on Programming Languages (2021)

Marco VassenaCraig DisselkoenKlaus von GleissenthallSunjay CauligiRami Gökhan KıcıRanjit JhalaDean TullsenDeian Stefan

computer sciencecryptographic codesoftware securityinformation securityspeculative leakscryptography

I See Dead µOps: Leaking Secrets via Intel/Amd Micro-Op Caches. (2021)

Xida RenLogan MoodyMohammadkazem TaramMatthew JordanDean M. TullsenAshish Venkat

computer sciencehigh performance computer architecturemicro-op cacheunauthorized secretmicroarchitecturedata securitycomputer engineeringcomputer securitycomputer architecturehardware security solutionhardware securityside-channel attacksdead µops

Not All Features Are Equal: Discovering Essential Features for Preserving Prediction Privacy. (2021)

Fatemehsadat MireshghallahMohammadkazem TaramAli JalaliAhmed Taha Taha ElthakebDean TullsenHadi Esmaeilzadeh

computer sciencebenchmark studiesknowledge discoveryprivacy-preserving communicationdeep learningadversarial machine learningprediction privacyessential featuresmachine learningmachine learning researchcomputational intelligencenatural language processinginformation retrievalpattern recognitionstatistics

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Dean Tullsen

Professor

University of California, San Diego

Affiliations

Jacobs School of Engineering

Computer Science & Engineering

Dean Tullsen is currently serving as a Computer Science & Engineering Professor at University of California, San Diego.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Dean Tullsen

University of California, San Diego

Professor

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

Hardware-Assisted Fault Isolation: Going Beyond the Limits of Software-Based Sandboxing. IEEE Micro (2024)

Shravan NarayanTal GarfinkelMohammadkazem TaramJoey RudekDaniel MoghimiEvan JohnsonChris FallinAnjo Vahldiek-OberwagnerMichael LeMayRavi SahitaDean TullsenDeian Stefan

systems engineeringmicro-electromechanical systemsengineeringmicro technologyelectrical engineeringflexible electronicshardware security

Hosein YavarzadehArchit AgarwalMax ChristmanChristina GarmanDaniel GenkinAndrew KwongDaniel MoghimiDeian StefanKazem TaramDean Tullsen

computer sciencehigh-resolution control-flow attackscomputer securityconditional branch predictormachine learning

PDIP: Priority Directed Instruction Prefetching. International Conference on Architectural Support for Programming Languages and Operating Systems (2024)

Bhargav Reddy GodalaSankara Prasad RameshGilles A. PokamJared StarkAndre SeznecDean TullsenDavid I. August

computer scienceinstruction prefetchingparallel computingoperating systemsscheduling (computing)

Half Half: Demystifying Intel’s Directional Branch Predictors for Fast, Secure Partitioned Execution. 2022 IEEE Symposium on Security and Privacy (SP) (2023)

Hosein YavarzadehMohammadkazem TaramShravan NarayanDeian StefanDean Tullsen

computer sciencedeep learningcomputer securitydirectional branch predictorsdemystifying intelmachine learning

EVAX: Towards a Practical, Pro-Active Adaptive Architecture for High Performance Security. IEEE/ACM International Symposium on Microarchitecture (2022)

Samira Mirbagher AjorpazDaniel MoghimiJeffrey Neal CollinsGilles PokamNael Abu-GhazalehDean Tullsen

systems engineeringhigh performanceadaptive architecturearchitecturecomputer securityhigh-performance architectures

Mitigating Speculative Execution Attacks via Context-Sensitive Fencing. IEEE Design and Test (2022)

Mohammadkazem TaramAshish VenkatDean Tullsen

AGON: A Scalable Competitive Scheduler for Large Heterogeneous Systems. arXiv (Cornell University) (2021)

Andreas ProdromouAshish VenkatDean M. Tullsen

Automatically Eliminating Speculative Leaks From Cryptographic Code With Blade. Proceedings of the ACM on Programming Languages (2021)

Marco VassenaCraig DisselkoenKlaus von GleissenthallSunjay CauligiRami Gökhan KıcıRanjit JhalaDean TullsenDeian Stefan

computer sciencecryptographic codesoftware securityinformation securityspeculative leakscryptography

I See Dead µOps: Leaking Secrets via Intel/Amd Micro-Op Caches. (2021)

Xida RenLogan MoodyMohammadkazem TaramMatthew JordanDean M. TullsenAshish Venkat

Not All Features Are Equal: Discovering Essential Features for Preserving Prediction Privacy. (2021)

Fatemehsadat MireshghallahMohammadkazem TaramAli JalaliAhmed Taha Taha ElthakebDean TullsenHadi Esmaeilzadeh

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