Ali Jannesari

Orcid: 0000-0001-8672-5317

Affiliations:
  • Iowa State University, Ames, USA
  • University of California Berkeley, CA, USA (former)
  • Technische Universität Darmstadt, Germany (former)
  • RWTH Aachen University, Germany (former)
  • Karlsruher Institut für Technologie, Germany (former)


According to our database1, Ali Jannesari authored at least 114 papers between 2008 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Unsupervised learning based object detection using Contrastive Learning.
CoRR, 2024

The Landscape and Challenges of HPC Research and LLMs.
CoRR, 2024

OMPGPT: A Generative Pre-trained Transformer Model for OpenMP.
CoRR, 2024

2023
Reducing branch divergence to speed up parallel execution of unit testing on GPUs.
J. Supercomput., November, 2023

Predicting number of threads using balanced datasets for openMP regions.
Computing, May, 2023

A region proposal algorithm using texture similarity and perceptual grouping.
J. Ambient Intell. Humaniz. Comput., 2023

LEFL: Low Entropy Client Sampling in Federated Learning.
CoRR, 2023

CompCodeVet: A Compiler-guided Validation and Enhancement Approach for Code Dataset.
CoRR, 2023

AUTOPARLLM: GNN-Guided Automatic Code Parallelization using Large Language Models.
CoRR, 2023

Bridging the Gap Between Foundation Models and Heterogeneous Federated Learning.
CoRR, 2023

Federated Foundation Models: Privacy-Preserving and Collaborative Learning for Large Models.
CoRR, 2023

Learning to Parallelize with OpenMP by Augmented Heterogeneous AST Representation.
CoRR, 2023

Interpreting Pretrained Source-code Models using Neuron Redundancy Analyses.
CoRR, 2023

GraphBinMatch: Graph-based Similarity Learning for Cross-Language Binary and Source Code Matching.
CoRR, 2023

ParaGraph: Weighted Graph Representation for Performance Optimization of HPC Kernels.
CoRR, 2023

Accelerating Domain-aware Deep Learning Models with Distributed Training.
CoRR, 2023

Optimal Deep Learning Model for UAVs: A Case Study.
Proceedings of the 26th International Symposium on Wireless Personal Multimedia Communications, 2023

Addressing Stale Gradients in Scalable Federated Deep Reinforcement Learning.
Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

Enhancing Heterogeneous Federated Learning with Knowledge Extraction and Multi-Model Fusion.
Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

PERFOGRAPH: A Numerical Aware Program Graph Representation for Performance Optimization and Program Analysis.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Domain-Aware Scalable Distributed Training for Geo-Spatiotemporal Data.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

Power Constrained Autotuning using Graph Neural Networks.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

OpenMP Offload Features and Strategies for High Performance across Architectures and Compilers.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

Integrating Information from Natural Language Parse Tree to Code Generation.
Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

Discerning Self-Supervised Learning and Weakly Supervised Learning.
Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

Performance Optimization using Multimodal Modeling and Heterogeneous GNN.
Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing, 2023

Evaluating and Optimizing the Effectiveness of Neural Machine Translation in Supporting Code Retrieval Models: A Study on the CAT Benchmark.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Heterogeneous Federated Learning using Dynamic Model Pruning and Adaptive Gradient.
Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

Optimizing Decentralized Learning with Local Heterogeneity using Topology Morphing and Clustering.
Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

2022
Addressing Data Heterogeneity in Decentralized Learning via Topological Pre-processing.
CoRR, 2022

Towards Seamless Management of AI Models in High-Performance Computing.
CoRR, 2022

Resource-Aware Heterogeneous Federated Learning using Neural Architecture Search.
CoRR, 2022

Resource-aware Federated Learning using Knowledge Extraction and Multi-model Fusion.
CoRR, 2022

Story Point Effort Estimation by Text Level Graph Neural Network.
CoRR, 2022

SPATL: Salient Parameter Aggregation and Transfer Learning for Heterogeneous Federated Learning.
Proceedings of the SC22: International Conference for High Performance Computing, 2022

Pattern-based Autotuning of OpenMP Loops using Graph Neural Networks.
Proceedings of the IEEE/ACM International Workshop on Artificial Intelligence and Machine Learning for Scientific Applications, 2022

Story Point Level Classification by Text Level Graph Neural Network.
Proceedings of the 2022 IEEE/ACM 1st International Workshop on Natural Language-Based Software Engineering (NLBSE 2022), 2022

Learning Intermediate Representations using Graph Neural Networks for NUMA and Prefetchers Optimization.
Proceedings of the 2022 IEEE International Parallel and Distributed Processing Symposium, 2022

Efficient Volume Estimation for Dynamic Environments using Deep Learning on the Edge.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

Scalable and Extensible Robinson-Foulds for Comparative Phylogenetics.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

Multi-View Learning for Parallelism Discovery of Sequential Programs.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2022

Temporal shift reinforcement learning.
Proceedings of the EuroMLSys '22: Proceedings of the 2nd European Workshop on Machine Learning and Systems, Rennes, France, April 5, 2022

Heterogeneous Graph Neural Networks for Software Effort Estimation.
Proceedings of the ESEM '22: ACM / IEEE International Symposium on Empirical Software Engineering and Measurement, Helsinki, Finland, September 19, 2022

2021
Reducing Energy in GPGPUs through Approximate Trivial Bypassing.
ACM Trans. Embed. Comput. Syst., 2021

A Shallow 1-D Convolution Neural Network for Fetal State Assessment Based on Cardiotocogram.
SN Comput. Sci., 2021

CLAWS: Contrastive Learning with hard Attention and Weak Supervision.
CoRR, 2021

SPATL: Salient Parameter Aggregation and Transfer Learning for Heterogeneous Clients in Federated Learning.
CoRR, 2021

Transfer Learning Approaches for Knowledge Discovery in Grid-based Geo-Spatiotemporal Data.
CoRR, 2021

Adaptive Dynamic Pruning for Non-IID Federated Learning.
CoRR, 2021

Interpretable UAV Collision Avoidance using Deep Reinforcement Learning.
CoRR, 2021

GNN-RL Compression: Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning.
CoRR, 2021

Building representative and balanced datasets of OpenMP parallel regions.
Proceedings of the 29th Euromicro International Conference on Parallel, 2021

A Learning-Based Scheduler for High Volume Processing in Data Warehouse Using Graph Neural Networks.
Proceedings of the Parallel and Distributed Computing, Applications and Technologies, 2021

Generating Context-Aware API Calls from Natural Language Description Using Neural Embeddings and Machine Translation.
Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering, 2021

A Vision Based Deep Reinforcement Learning Algorithm for UAV Obstacle Avoidance.
Proceedings of the Intelligent Systems and Applications, 2021

DeepRace: A learning-based data race detector.
Proceedings of the 14th IEEE International Conference on Software Testing, 2021

An Empirical Study of Parallelizing Test Execution Using CUDA Unified Memory and OpenMP GPU Offloading.
Proceedings of the 14th IEEE International Conference on Software Testing, 2021

Auto Graph Encoder-Decoder for Neural Network Pruning.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Auto Graph Encoder-Decoder for Model Compression and Network Acceleration.
CoRR, 2020

HydroDeep - A Knowledge Guided Deep Neural Network for Geo-Spatiotemporal Data Analysis.
CoRR, 2020

Static Neural Compiler Optimization via Deep Reinforcement Learning.
CoRR, 2020

Multi-Class Cardiovascular Diseases Diagnosis from Electrocardiogram Signals using 1-D Convolution Neural Network.
Proceedings of the 21st International Conference on Information Reuse and Integration for Data Science, 2020

Accelerating winograd convolutions using symbolic computation and meta-programming.
Proceedings of the EuroSys '20: Fifteenth EuroSys Conference 2020, 2020

Skipping Non-essential Instructions Makes Data-Dependence Profiling Faster.
Proceedings of the Euro-Par 2020: Parallel Processing, 2020

Q-Flink: A QoS-Aware Controller for Apache Flink.
Proceedings of the 20th IEEE/ACM International Symposium on Cluster, 2020

2019
The Art of Getting Deep Neural Networks in Shape.
ACM Trans. Archit. Code Optim., 2019

A Simulation of UAV Power Optimization via Reinforcement Learning.
CoRR, 2019

DeepRace: Finding Data Race Bugs via Deep Learning.
CoRR, 2019

Automatic Repair and Type Binding of Undeclared Variables using Neural Networks.
CoRR, 2019

Efficient Object Detection Model for Real-Time UAV Applications.
CoRR, 2019

Dissecting sequential programs for parallelization - An approach based on computational units.
Concurr. Comput. Pract. Exp., 2019

Real-Time Stream Data Processing at Scale.
Proceedings of the 20th International Conference on Parallel and Distributed Computing, 2019

Dynamic Control of CPU Cap Allocations in Stream Processing and Data-Flow Platforms.
Proceedings of the 18th IEEE International Symposium on Network Computing and Applications, 2019

Automatic construct selection and variable classification in OpenMP.
Proceedings of the ACM International Conference on Supercomputing, 2019

Enhancing the Programmability and Performance Portability of GPU Tensor Operations.
Proceedings of the Euro-Par 2019: Parallel Processing, 2019

Accelerating Data-Dependence Profiling with Static Hints.
Proceedings of the Euro-Par 2019: Parallel Processing, 2019

2018
Improving performance of transactional memory through machine learning.
Concurr. Comput. Pract. Exp., 2018

Unveiling Thread Communication Bottlenecks Using Hardware-Independent Metrics.
Proceedings of the 47th International Conference on Parallel Processing, 2018

2017
Editorial of special issue on Software Engineering for Parallel Systems.
J. Syst. Softw., 2017

Brief Announcement: Meeting the Challenges of Parallelizing Sequential Programs.
Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures, 2017

Parallelizing Audio Analysis Applications - A Case Study.
Proceedings of the 39th IEEE/ACM International Conference on Software Engineering: Software Engineering Education and Training Track, 2017

Boda: A Holistic Approach for Implementing Neural Network Computations.
Proceedings of the Computing Frontiers Conference, 2017

2016
Unveiling parallelization opportunities in sequential programs.
J. Syst. Softw., 2016

Automatic Generation of Unit Tests for Correlated Variables in Parallel Programs.
Int. J. Parallel Program., 2016

A Metaprogramming and Autotuning Framework for Deploying Deep Learning Applications.
CoRR, 2016

Improving Performance of Transactional Applications through Adaptive Transactional Memory.
Proceedings of the 24th Euromicro International Conference on Parallel, 2016

Automatic Parallel Pattern Detection in the Algorithm Structure Design Space.
Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium, 2016

2015
Resource and application-aware resource discovery in computing environments.
J. Supercomput., 2015

Detection of High-Level Synchronization Anomalies in Parallel Programs.
Int. J. Parallel Program., 2015

Workshop Preview of the 2nd International Workshop on Software for Parallel Systems (SEPS 2015).
Proceedings of the Companion Proceedings of the 2015 ACM SIGPLAN International Conference on Systems, 2015

An Efficient Data-Dependence Profiler for Sequential and Parallel Programs.
Proceedings of the 2015 IEEE International Parallel and Distributed Processing Symposium, 2015

Combining Unit Tests for Data Race Detection.
Proceedings of the 10th IEEE/ACM International Workshop on Automation of Software Test, 2015

Characterizing Loop-Level Communication Patterns in Shared Memory.
Proceedings of the 44th International Conference on Parallel Processing, 2015

Automatic Optimization of Software Transactional Memory Through Linear Regression and Decision Tree.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2015

Beyond Data Parallelism: Identifying Parallel Tasks in Sequential Programs.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2015

Fast Data-Dependence Profiling by Skipping Repeatedly Executed Memory Operations.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2015

Dependence-Based Code Transformation for Coarse-Grained Parallelism.
Proceedings of the 2015 International Workshop on Code Optimisation for Multi and Many Cores, 2015

The Basic Building Blocks of Parallel Tasks.
Proceedings of the 2015 International Workshop on Code Optimisation for Multi and Many Cores, 2015

2014
Library-Independent Data Race Detection.
IEEE Trans. Parallel Distributed Syst., 2014

Using Template Matching to Infer Parallel Design Patterns.
ACM Trans. Archit. Code Optim., 2014

Generating Classified Parallel Unit Tests.
Proceedings of the Tests and Proofs - 8th International Conference, 2014

SEPS 2014: first international workshop on software engineering for parallel systems.
Proceedings of the SPLASH'14, 2014

2013
Automatic generation of parallel unit tests.
Proceedings of the 8th International Workshop on Automation of Software Test, 2013

Discovery of Potential Parallelism in Sequential Programs.
Proceedings of the 42nd International Conference on Parallel Processing, 2013

Detecting Correlation Violations and Data Races by Inferring Non-deterministic Reads.
Proceedings of the 19th IEEE International Conference on Parallel and Distributed Systems, 2013

Predicting Parallelization of Sequential Programs Using Supervised Learning.
Proceedings of the 12th International Conference on Machine Learning and Applications, 2013

2011
Dynamic Data Race Detection for Correlated Variables.
Proceedings of the Algorithms and Architectures for Parallel Processing, 2011

2010
Dynamic race detection in parallel programs.
PhD thesis, 2010

Identifying ad-hoc synchronization for enhanced race detection.
Proceedings of the 24th IEEE International Symposium on Parallel and Distributed Processing, 2010

2009
Parallelizing Bzip2: A Case Study in Multicore Software Engineering.
IEEE Softw., 2009

Helgrind+: An efficient dynamic race detector.
Proceedings of the 23rd IEEE International Symposium on Parallel and Distributed Processing, 2009

2008
On-the-fly race detection in multi-threaded programs.
Proceedings of the 6th Workshop on Parallel and Distributed Systems: Testing, 2008

Software engineering for multicore systems: an experience report.
Proceedings of the 1st International Workshop on Multicore Software Engineering, 2008


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