Grigori Fursin

Orcid: 0000-0001-7719-1624

According to our database1, Grigori Fursin authored at least 54 papers between 2002 and 2023.

Collaborative distances:

Timeline

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Bibliography

2023
Federated benchmarking of medical artificial intelligence with MedPerf.
Nat. Mac. Intell., July, 2023

2021
On the Anatomy of Predictive Models for Accelerating GPU Convolution Kernels and Beyond.
ACM Trans. Archit. Code Optim., 2021

MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation.
CoRR, 2021

Workflows Community Summit: Advancing the State-of-the-art of Scientific Workflows Management Systems Research and Development.
CoRR, 2021

Workflows Community Summit: Bringing the Scientific Workflows Community Together.
CoRR, 2021


2020
Collective Knowledge: organizing research projects as a database of reusable components and portable workflows with common APIs.
CoRR, 2020

The Collective Knowledge project: making ML models more portable and reproducible with open APIs, reusable best practices and MLOps.
CoRR, 2020

CodeReef: an open platform for portable MLOps, reusable automation actions and reproducible benchmarking.
CoRR, 2020

2019
SysML: The New Frontier of Machine Learning Systems.
CoRR, 2019

SysML'19 demo: customizable and reusable Collective Knowledge pipelines to automate and reproduce machine learning experiments.
CoRR, 2019

2018
A model-driven approach for a new generation of adaptive libraries.
CoRR, 2018

A Collective Knowledge workflow for collaborative research into multi-objective autotuning and machine learning techniques.
CoRR, 2018

Introducing ReQuEST: an Open Platform for Reproducible and Quality-Efficient Systems-ML Tournaments.
CoRR, 2018

Invited Talk Abstract: Introducing ReQuEST: An Open Platform for Reproducible and Quality-Efficient Systems-ML Tournaments.
Proceedings of the 1st Workshop on Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications, 2018

Multi-objective autotuning of MobileNets across the full software/hardware stack.
Proceedings of the 1st on Reproducible Quality-Efficient Systems Tournament on Co-designing Pareto-efficient Deep Learning, 2018

PANEL: Open panel and discussion on tackling complexity, reproducibility and tech transfer challenges in a rapidly evolving AI/ML/systems research.
Proceedings of the 1st on Reproducible Quality-Efficient Systems Tournament on Co-designing Pareto-efficient Deep Learning, 2018

2016
Benchmarking, autotuning and crowdtuning OpenCL programs using the Collective Knowledge framework.
Proceedings of the 4th International Workshop on OpenCL, 2016

Optimizing convolutional neural networks on embedded platforms with OpenCL.
Proceedings of the 4th International Workshop on OpenCL, 2016

Collective Knowledge: Towards R&D sustainability.
Proceedings of the 2016 Design, Automation & Test in Europe Conference & Exhibition, 2016

2015
Artifact Evaluation for Publications (Dagstuhl Perspectives Workshop 15452).
Dagstuhl Reports, 2015

Collective Mind, Part II: Towards Performance- and Cost-Aware Software Engineering as a Natural Science.
CoRR, 2015

2014
Collective mind: Towards practical and collaborative auto-tuning.
Sci. Program., 2014

Finding representative sets of optimizations for adaptive multiversioning applications.
CoRR, 2014

Collective Tuning Initiative.
CoRR, 2014

Proceedings of the 5th International Workshop on Adaptive Self-tuning Computing Systems 2015 (ADAPT'15).
CoRR, 2014

Community-driven reviewing and validation of publications.
Proceedings of the 1st ACM SIGPLAN Workshop on Reproducible Research Methodologies and New Publication Models in Computer Engineering, 2014

2013
Collective Mind: cleaning up the research and experimentation mess in computer engineering using crowdsourcing, big data and machine learning.
CoRR, 2013

Crowdtuning: systematizing auto-tuning using predictive modeling and crowdsourcing.
Proceedings of the Parallel Computing: Accelerating Computational Science and Engineering (CSE), 2013

2012
Deconstructing iterative optimization.
ACM Trans. Archit. Code Optim., 2012

Poster: Collective Tuning: Novel Extensible Methodology, Framework and Public Repository to Collaboratively Address Exascale Challenges.
Proceedings of the 2012 SC Companion: High Performance Computing, 2012

Abstract: cTuning.org: Novel Extensible Methodology, Framework and Public Repository to Collaboratively Address Exascale Challenges.
Proceedings of the 2012 SC Companion: High Performance Computing, 2012

2011
Milepost GCC: Machine Learning Enabled Self-tuning Compiler.
Int. J. Parallel Program., 2011

2010
Collective optimization: A practical collaborative approach.
ACM Trans. Archit. Code Optim., 2010

Evaluating iterative optimization across 1000 datasets.
Proceedings of the 2010 ACM SIGPLAN Conference on Programming Language Design and Implementation, 2010

Practical aggregation of semantical program properties for machine learning based optimization.
Proceedings of the 2010 International Conference on Compilers, 2010

2009
Systematic search within an optimisation space based on Unified Transformation Framework.
Int. J. Comput. Sci. Eng., 2009

Portable compiler optimisation across embedded programs and microarchitectures using machine learning.
Proceedings of the 42st Annual IEEE/ACM International Symposium on Microarchitecture (MICRO-42 2009), 2009

Reducing Training Time in a One-Shot Machine Learning-Based Compiler.
Proceedings of the Languages and Compilers for Parallel Computing, 2009

Predictive Runtime Code Scheduling for Heterogeneous Architectures.
Proceedings of the High Performance Embedded Architectures and Compilers, 2009

Collective Optimization.
Proceedings of the High Performance Embedded Architectures and Compilers, 2009

2007
Quick and Practical Run-Time Evaluation of Multiple Program Optimizations.
Trans. High Perform. Embed. Archit. Compil., 2007

A Cost-Aware Parallel Workload Allocation Approach Based on Machine Learning Techniques.
Proceedings of the Network and Parallel Computing, IFIP International Conference, 2007

MiDataSets: Creating the Conditions for a More Realistic Evaluation of Iterative Optimization.
Proceedings of the High Performance Embedded Architectures and Compilers, 2007

Rapidly Selecting Good Compiler Optimizations using Performance Counters.
Proceedings of the Fifth International Symposium on Code Generation and Optimization (CGO 2007), 2007

Fast compiler optimisation evaluation using code-feature based performance prediction.
Proceedings of the 4th Conference on Computing Frontiers, 2007

2006
Using Machine Learning to Focus Iterative Optimization.
Proceedings of the Fourth IEEE/ACM International Symposium on Code Generation and Optimization (CGO 2006), 2006

Automatic performance model construction for the fast software exploration of new hardware designs.
Proceedings of the 2006 International Conference on Compilers, 2006

2005
Probabilistic source-level optimisation of embedded programs.
Proceedings of the 2005 ACM SIGPLAN/SIGBED Conference on Languages, 2005

A Heuristic Search Algorithm Based on Unified Transformation Framework.
Proceedings of the 34th International Conference on Parallel Processing Workshops (ICPP 2005 Workshops), 2005

A Practical Method for Quickly Evaluating Program Optimizations.
Proceedings of the High Performance Embedded Architectures and Compilers, 2005

2004
Iterative compilation and performance prediction for numerical applications.
PhD thesis, 2004

A fast and accurate method for determining a lower bound on execution time.
Concurr. Comput. Pract. Exp., 2004

2002
Evaluating Iterative Compilation.
Proceedings of the Languages and Compilers for Parallel Computing, 15th Workshop, 2002


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