Mustafa Abduljabbar
Computer Science · The Ohio State University
Publications
53
Citations
196
Est. group size
~16
Recurring co-author estimate
Active years
14
Publishing since 2012
Mustafa Abduljabbar works on parallel and distributed computing, focusing on how to efficiently schedule and run computational tasks across different types of hardware, including multicore CPUs, edge devices, and heterogeneous systems that combine CPUs with accelerators. His work spans scheduling algorithms, energy-efficient task management, and running AI models (like CNNs) efficiently on resource-constrained devices, as well as large-scale scientific computing methods for simulating physical phenomena.
Publication output was modest and fairly steady from 2017-2021, then increased notably from 2022 through 2024 before appearing to taper in 2025.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Parallel Programming Models
2024
- Designing Converged Middleware for HPC, AI, and Big Data: Challenges and Opportunities
Lecture notes in networks and systems · 2024
- Performance Characterization of using Quantization for DNN Inference on Edge Devices: Extended Version
arXiv (Cornell University) · 2023
- Shisha: Online Scheduling of CNN Pipelines on Heterogeneous Architectures
Lecture notes in computer science · 2023
- ERASE: Energy Efficient Task Mapping and Resource Management for Work Stealing Runtimes
ACM Transactions on Architecture and Code Optimization · 2022
- STEER: Asymmetry-aware Energy Efficient Task Scheduler for Cluster-based Multicore Architectures
2022
- Shisha: Online scheduling of CNN pipelines on heterogeneous architectures
arXiv (Cornell University) · 2022
- Parallel Programming Models
2022
- An online guided tuning approach to run CNN pipelines on edge devices
2021
- Mitigating inefficient task mappings with an Adaptive Resource-Moldable Scheduler (ARMS)
arXiv (Cornell University) · 2021
- LEGaTO: Low-Energy, Secure, and Resilient Toolset for Heterogeneous Computing
2020
- Abstraction Layer For Standardizing APIs of Task-Based Engines
IEEE Transactions on Parallel and Distributed Systems · 2020
- Scheduling Task-parallel Applications in Dynamically Asymmetric Environments
2020
- Scheduling Task-parallel Applications in Dynamically Asymmetric Environments
arXiv (Cornell University) · 2020
- Extreme Scale FMM-Accelerated Boundary Integral Equation Solver for Wave Scattering
SIAM Journal on Scientific Computing · 2019
- arXiv (Cornell University)×12
- Lecture notes in computer science×3
- IEEE Micro×2
- ACM Transactions on Architecture and Code Optimization×1
- Concurrency and Computation Practice and Experience×1
- Aamir Shafi
Computer Science · The Ohio State University
- Mengchi Zhang
Computer Science · Purdue University West Lafayette
- Matthew Anderson
Computer Science · Indiana University
- Tu Tran
Computer Science · The Ohio State University
- Thomas Sterling
Computer Science · Indiana University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 19, 2026.
Claim or correct this profile