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ORCIDGagan Agrawal
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- affiliation: Ohio State University, Columbus, USA
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2020 – today
- 2024
[c280]Wei Niu
, Gagan Agrawal, Bin Ren:
SoD2: Statically Optimizing Dynamic Deep Neural Network Execution. ASPLOS (1) 2024: 386-400- [c279]Wei Niu, Md. Musfiqur Rahman Sanim, Zhihao Shu, Jiexiong Guan, Xipeng Shen, Miao Yin, Gagan Agrawal, Bin Ren:
SmartMem: Layout Transformation Elimination and Adaptation for Efficient DNN Execution on Mobile. ASPLOS (3) 2024: 916-931 - [c278]Gagan Agrawal, Alba Cristina Melo:
Message from the 2024 General Co-chairs. IPDPS (Workshops) 2024: xxviii-xxix - [c277]Mahdieh Heidaripour, Ladan Kian, Maryam Rezapour, Mark Holcomb, Benjamin Fuller, Gagan Agrawal, Hoda Maleki:
Organizing Records for Retrieval in Multi-Dimensional Range Searchable Encryption. SECRYPT 2024: 459-466 - [i11]Wei Niu, Gagan Agrawal, Bin Ren:
SoD2: Statically Optimizing Dynamic Deep Neural Network. CoRR abs/2403.00176 (2024) - [i10]Wei Niu, Md. Musfiqur Rahman Sanim, Zhihao Shu, Jiexiong Guan, Xipeng Shen, Miao Yin, Gagan Agrawal, Bin Ren:
SmartMem: Layout Transformation Elimination and Adaptation for Efficient DNN Execution on Mobile. CoRR abs/2404.13528 (2024) - [i9]Mahdieh Heidaripour, Ladan Kian, Maryam Rezapour, Mark Holcomb, Benjamin Fuller, Gagan Agrawal, Hoda Maleki:
Organizing Records for Retrieval in Multi-Dimensional Range Searchable Encryption. IACR Cryptol. ePrint Arch. 2024: 635 (2024) - 2023
- [c276]Xiang Li, Gagan Agrawal, Ruoming Jin, Rajiv Ramnath:
Scalable Deep Metric Learning on Attributed Graphs. CSoNet 2023: 385-397 - [c275]Braxton Bolt, Hoda Maleki, Gagan Agrawal, Jeffrey D. Morris, Khan Farabi:
SecFob: A Remote Keyless Entry Security Solution. ISC2 2023: 1-7 - [c274]Yang Xia, Peng Jiang, Gagan Agrawal, Rajiv Ramnath:
End-to-End LU Factorization of Large Matrices on GPUs. PPoPP 2023: 288-300 - [c273]Asma Jodeiri Akbarfam, Mahdieh Heidaripour, Hoda Maleki, Gokila Dorai, Gagan Agrawal:
ForensiBlock: A Provenance-Driven Blockchain Framework for Data Forensics and Auditability. TPS-ISA 2023: 136-145 - [i8]Asma Jodeiri Akbarfam, Mahdieh Heidaripour, Hoda Maleki, Gokila Dorai, Gagan Agrawal:
ForensiBlock: A Provenance-Driven Blockchain Framework for Data Forensics and Auditability. CoRR abs/2308.03927 (2023) - 2022
- [c272]Haoyuan Xing, Gagan Agrawal, Rajiv Ramnath:
GPU Adaptive In-situ Parallel Analytics (GAP). PACT 2022: 467-480 - [c271]Xiang Li, Dong Li, Ruoming Jin, Rajiv Ramnath, Gagan Agrawal:
Deep Graph Clustering with Random-walk based Scalable Learning. ASONAM 2022: 88-95 - [c270]Md Hasan, Hoda Maleki, Gagan Agrawal:
Securing Pseudonym Schemes for Vehicular Privacy. IEEE Big Data 2022: 6647-6649 - [c269]Yang Xia, Peng Jiang, Gagan Agrawal, Rajiv Ramnath:
Scaling and Selecting GPU Methods for All Pairs Shortest Paths (APSP) Computations. IPDPS 2022: 190-200 - [c268]Wei Niu, Jiexiong Guan, Xipeng Shen, Yanzhi Wang, Gagan Agrawal, Bin Ren:
GCD2: A Globally Optimizing Compiler for Mapping DNNs to Mobile DSPs. MICRO 2022: 512-529 - 2021
- [c267]Renhao Cui, Gagan Agrawal, Rajiv Ramnath:
Constraint-embedded paraphrase generation for commercial tweets. ASONAM 2021: 369-376 - [c266]Dane Troyer, Justin Henry, Hoda Maleki, Gokila Dorai, Bethany Sumner, Gagan Agrawal, Jon Ingram:
Privacy-Preserving Framework to Facilitate Shared Data Access for Wearable Devices. IEEE BigData 2021: 2583-2592 - [c265]Jia Guo, Radu Teodorescu, Gagan Agrawal:
Fused DSConv: Optimizing Sparse CNN Inference for Execution on Edge Devices. CCGRID 2021: 545-554 - [c264]Xiang Li, Ruoming Jin, Rajiv Ramnath, Gagan Agrawal:
A Framework for Accelerating Graph Convolutional Networks on Massive Datasets. CSoNet 2021: 79-92 - [c263]Xiang Li, Gagan Agrawal:
Shrinking Sample Search Algorithm for Automatic Tuning of GPU Kernels. HiPC 2021: 262-271 - [c262]Shuangsheng Lou, Gagan Agrawal:
A Programming API Implementation for Secure Data Analytics Applications with Homomorphic Encryption on GPUs. HiPC 2021: 418-423 - [c261]Jia Guo, Radu Teodorescu, Gagan Agrawal:
A Fused Inference Design for Pattern-Based Sparse CNN on Edge Devices. HiPC 2021: 424-429 - [c260]Shuangsheng Lou, Gagan Agrawal:
Mapping IoT Applications on the Edge to Cloud Continuum with a Filter Stream Model. ICFEC 2021: 61-65 - [c259]Yang Xia, Peng Jiang, Gagan Agrawal, Rajiv Ramnath:
Scaling Sparse Matrix Multiplication on CPU-GPU Nodes. IPDPS 2021: 392-401 - [c258]Wei Niu, Jiexiong Guan, Yanzhi Wang, Gagan Agrawal, Bin Ren:
DNNFusion: accelerating deep neural networks execution with advanced operator fusion. PLDI 2021: 883-898 - [c257]Gangyi Zhu, Gagan Agrawal:
Sampling-based Sparse Format Selection on GPUs. SBAC-PAD 2021: 198-208 - [c256]Shuangsheng Lou, Nisha Panwar, Gagan Agrawal:
Integrity Verification for Streaming IoT Applications with a Minimalist Logging Scheme. SMARTCOMP 2021: 197-202 - [i7]Wei Niu, Jiexiong Guan, Yanzhi Wang, Gagan Agrawal, Bin Ren:
DNNFusion: Accelerating Deep Neural Networks Execution with Advanced Operator Fusion. CoRR abs/2108.13342 (2021) - [i6]Xiang Li, Dong Li, Ruoming Jin, Gagan Agrawal, Rajiv Ramnath:
Scalable Deep Graph Clustering with Random-walk based Self-supervised Learning. CoRR abs/2112.15530 (2021) - 2020
- [j35]Roee Ebenstein, Gagan Agrawal:
DistriPlan: an optimized join execution framework for geo-distributed scientific data. Distributed Parallel Databases 38(1): 127-152 (2020) - [j34]Renhao Cui, Gagan Agrawal, Rajiv Ramnath:
Tweets can tell: activity recognition using hybrid gated recurrent neural networks. Soc. Netw. Anal. Min. 10(1): 16 (2020) - [j33]Peng Jiang, Yang Xia, Gagan Agrawal:
Combining SIMD and Many/Multi-core Parallelism for Finite-state Machines with Enumerative Speculation. ACM Trans. Parallel Comput. 7(3): 15:1-15:26 (2020) - [c255]Jia Guo, Radu Teodorescu, Gagan Agrawal:
A Pattern-Based API for Mapping Applications to a Hierarchy of Multi-Core Devices. CCGRID 2020: 11-20 - [c254]Ruoming Jin, Zhen Peng, Wendell Wu, Feodor F. Dragan, Gagan Agrawal, Bin Ren:
Parallelizing pruned landmark labeling: dealing with dependencies in graph algorithms. ICS 2020: 11:1-11:13 - [c253]Jia Guo, Gagan Agrawal:
Smart Streaming: A High-Throughput Fault-tolerant Online Processing System. IPDPS Workshops 2020: 396-405 - [c252]Yang Xia, Peng Jiang, Gagan Agrawal:
Scaling out speculative execution of finite-state machines with parallel merge. PPoPP 2020: 160-172 - [c251]Peng Jiang, Changwan Hong, Gagan Agrawal:
A novel data transformation and execution strategy for accelerating sparse matrix multiplication on GPUs. PPoPP 2020: 376-388 - [c250]Haoyuan Xing, Gagan Agrawal, Rajiv Ramnath:
MoHA: a composable system for efficient in-situ analytics on heterogeneous HPC systems. SC 2020: 82 - [i5]Peng Jiang, Gagan Agrawal:
Adaptive Periodic Averaging: A Practical Approach to Reducing Communication in Distributed Learning. CoRR abs/2007.06134 (2020)
2010 – 2019
- 2019
- [c249]Gangyi Zhu, Peng Jiang, Gagan Agrawal:
A Methodology for Characterizing Sparse Datasets and Its Application to SIMD Performance Prediction. PACT 2019: 445-456 - [c248]Renhao Cui, Gagan Agrawal, Rajiv Ramnath:
Tweets can tell: activity recognition using hybrid long short-term memory model. ASONAM 2019: 164-167 - [c247]Yang Xia, Peng Jiang, Gagan Agrawal:
Enabling prefix sum parallelism pattern for recurrences with principled function reconstruction. CC 2019: 17-28 - [c246]Peng Jiang, Gagan Agrawal:
Accelerating distributed stochastic gradient descent with adaptive periodic parameter averaging: poster. PPoPP 2019: 403-404 - [c245]Haoyuan Xing, Gagan Agrawal:
Accelerating array joining with integrated value-index. SSDBM 2019: 145-156 - [i4]Ruoming Jin, Zhen Peng, Wendell Wu, Feodor F. Dragan, Gagan Agrawal, Bin Ren:
Pruned Landmark Labeling Meets Vertex Centric Computation: A Surprisingly Happy Marriage! CoRR abs/1906.12018 (2019) - [i3]Renhao Cui, Gagan Agrawal, Rajiv Ramnath:
Tweets Can Tell: Activity Recognition using Hybrid Long Short-Term Memory Model. CoRR abs/1908.02551 (2019) - [i2]Renhao Cui, Gagan Agrawal, Rajiv Ramnath:
Towards Successful Social Media Advertising: Predicting the Influence of Commercial Tweets. CoRR abs/1910.12446 (2019) - 2018
- [c244]Peng Jiang, Linchuan Chen, Gagan Agrawal:
Revealing parallel scans and reductions in recurrences through function reconstruction. PACT 2018: 10:1-10:13 - [c243]Peng Jiang, Gagan Agrawal:
Conflict-free vectorization of associative irregular applications with recent SIMD architectural advances. CGO 2018: 175-187 - [c242]Roee Ebenstein, Gagan Agrawal, Jiali Wang, Joshua M. Boley, Rajkumar Kettimuthu:
FDQ: Advance Analytics Over Real Scientific Array Datasets. eScience 2018: 453-463 - [c241]Muhammed Emin Ozturk, Marissa Renardy, Yukun Li, Gagan Agrawal, Ching-Shan Chou:
A Novel Approach for Handling Soft Error in Conjugate Gradients. HiPC 2018: 193-202 - [c240]Gangyi Zhu, Gagan Agrawal:
A Performance Prediction Framework for Irregular Applications. HiPC 2018: 304-313 - [c239]Jia Guo, Gagan Agrawal:
Achieving Performance and Programmability for MapReduce(-Like) Frameworks. HiPC 2018: 314-323 - [c238]Peng Jiang, Gagan Agrawal:
A Linear Speedup Analysis of Distributed Deep Learning with Sparse and Quantized Communication. NeurIPS 2018: 2530-2541 - [c237]Peng Jiang, Gagan Agrawal:
Revealing parallel scans and reductions in sequential loops through function reconstruction. PPoPP 2018: 395-396 - [c236]Haoyuan Xing, Gagan Agrawal:
COMPASS: compact array storage with value index. SSDBM 2018: 7:1-7:12 - 2017
- [c235]Jiaqi Liu, Gagan Agrawal:
Supporting Fault-Tolerance in Presence of In-Situ Analytics. CCGrid 2017: 304-313 - [c234]Peng Jiang, Gagan Agrawal:
Efficient SIMD and MIMD parallelization of hash-based aggregation by conflict mitigation. ICS 2017: 24:1-24:11 - [c233]Mücahid Kutlu, Gagan Agrawal, James S. Blachly:
Par-eXpress: A Tool for Analysis of Sequencing Experiments With Ambiguous Assignment of Fragments in Parallel. IPDPS Workshops 2017: 303-310 - [c232]Peng Jiang, Gagan Agrawal:
Combining SIMD and Many/Multi-core Parallelism for Finite State Machines with Enumerative Speculation. PPoPP 2017: 179-191 - [c231]Roee Ebenstein, Gagan Agrawal:
DistriPlan: An Optimized Join Execution Framework for Geo-Distributed Scientific Data. SSDBM 2017: 25:1-25:6 - 2016
- [j32]Mehmet Can Kurt, Sriram Krishnamoorthy, Gagan Agrawal, Bin Ren:
User-Assisted Store Recycling for Dynamic Task Graph Schedulers. ACM Trans. Archit. Code Optim. 13(4): 55:1-55:24 (2016) - [c230]Linchuan Chen, Peng Jiang, Gagan Agrawal:
Exploiting recent SIMD architectural advances for irregular applications. CGO 2016: 47-58 - [c229]David Siegal, Jia Guo, Gagan Agrawal:
Smart-MLlib: A High-Performance Machine-Learning Library. CLUSTER 2016: 336-345 - [c228]Jiaqi Liu, Gagan Agrawal:
Soft Error Detection for Iterative Applications Using Offline Training. HiPC 2016: 2-11 - [c227]Sameh Shohdy, Abhinav Vishnu, Gagan Agrawal:
Fault Tolerant Frequent Pattern Mining. HiPC 2016: 12-21 - [c226]Renhao Cui, Gagan Agrawal, Rajiv Ramnath, Vinh Ngoc Khuc:
Ensemble of Heterogeneous Classifiers for Improving Automated Tweet Classification. ICDM Workshops 2016: 1045-1052 - [c225]Sameh Shohdy, Abhinav Vishnu, Gagan Agrawal:
Fault Tolerant Support Vector Machines. ICPP 2016: 598-607 - [c224]Peng Jiang, Linchuan Chen, Gagan Agrawal:
Reusing Data Reorganization for Efficient SIMD Parallelization of Adaptive Irregular Applications. ICS 2016: 16:1-16:10 - [c223]Rajkumar Kettimuthu, Gagan Agrawal, P. Sadayappan, Ian T. Foster:
Differentiated Scheduling of Response-Critical and Best-Effort Wide-Area Data Transfers. IPDPS 2016: 1113-1122 - [c222]Mehmet Can Kurt, Bin Ren, Sriram Krishnamoorthy, Gagan Agrawal:
User-assisted storage reuse determination for dynamic task graphs. PPoPP 2016: 54:1-54:2 - [i1]Sameh Shohdy, Abhinav Vishnu, Gagan Agrawal:
Fault Tolerant Frequent Pattern Mining. CoRR abs/1610.05116 (2016) - 2015
- [c221]Roee Ebenstein, Gagan Agrawal:
DSDQuery DSI - Querying scientific data repositories with structured operators. IEEE BigData 2015: 485-492 - [c220]Manirupa Das, Renhao Cui, David R. Campbell, Gagan Agrawal, Rajiv Ramnath:
Towards methods for systematic research on big data. IEEE BigData 2015: 2072-2081 - [c219]Jiaqi Liu, Mehmet Can Kurt, Gagan Agrawal:
A Practical Approach for Handling Soft Errors in Iterative Applications. CLUSTER 2015: 158-161 - [c218]Mücahid Kutlu, Gagan Agrawal:
RE-PAGE: Domain-Specific REplication and PArallel Processing of GEnomic Data. CLUSTER 2015: 332-341 - [c217]Tekin Bicer, Doga Gürsoy, Rajkumar Kettimuthu, Francesco De Carlo, Gagan Agrawal, Ian T. Foster:
Rapid Tomographic Image Reconstruction via Large-Scale Parallelization. Euro-Par 2015: 289-302 - [c216]Sameh Shohdy, Yu Su, Gagan Agrawal:
Load Balancing and Accelerating Parallel Spatial Join Operations Using Bitmap Indexing. HiPC 2015: 396-405 - [c215]Jiaqi Liu, Gagan Agrawal:
Algorithm Level Fault Tolerance for Molecular Dynamic Applications. HiPC 2015: 406-415 - [c214]Yu Su, Yi Wang, Gagan Agrawal:
In-Situ Bitmaps Generation and Efficient Data Analysis based on Bitmaps. HPDC 2015: 61-72 - [c213]Mücahid Kutlu, Gagan Agrawal:
GEM: A Framework for Developing Shared-Memory Parallel Genomic Applications on Memory Constrained Architectures. ICPP 2015: 829-838 - [c212]Linchuan Chen, Xin Huo, Gagan Agrawal:
A Pattern Specification and Optimizations Framework for Accelerating Scientific Computations on Heterogeneous Clusters. IPDPS 2015: 591-600 - [c211]Linchuan Chen, Xin Huo, Bin Ren, Surabhi Jain, Gagan Agrawal:
Efficient and Simplified Parallel Graph Processing over CPU and MIC. IPDPS 2015: 819-828 - [c210]Mehmet Can Kurt, Bin Ren, Gagan Agrawal:
Low-Overhead Fault-Tolerance Support Using DISC Programming Model. LCPC 2015: 20-36 - [c209]Bin Ren, Nishkam Ravi, Yi Yang, Min Feng, Gagan Agrawal, Srimat T. Chakradhar:
Automatic and Efficient Data Host-Device Communication for Many-Core Coprocessors. LCPC 2015: 173-190 - [c208]Yi Wang, Linchuan Chen, Gagan Agrawal:
Supporting online analytics with user-defined estimation and early termination in a MapReduce-like framework. DISCS@SC 2015: 8:1-8:8 - [c207]Rajkumar Kettimuthu, Gayane Vardoyan, Gagan Agrawal, P. Sadayappan, Ian T. Foster:
An elegant sufficiency: load-aware differentiated scheduling of data transfers. SC 2015: 46:1-46:12 - [c206]Yi Wang, Gagan Agrawal, Tekin Bicer, Wei Jiang:
Smart: a MapReduce-like framework for in-situ scientific analytics. SC 2015: 51:1-51:12 - [c205]Yi Wang, Yu Su, Gagan Agrawal:
A novel approach for approximate aggregations over arrays. SSDBM 2015: 4:1-4:12 - [c204]Gangyi Zhu, Yi Wang, Gagan Agrawal:
SciCSM: novel contrast set mining over scientific datasets using bitmap indices. SSDBM 2015: 38:1-38:6 - 2014
- [j31]Yu Su, Gagan Agrawal, Jonathan Woodring, Kary L. Myers, Joanne Wendelberger, James P. Ahrens:
Effective and efficient data sampling using bitmap indices. Clust. Comput. 17(4): 1081-1100 (2014) - [j30]Bin Ren, Todd Mytkowicz, Gagan Agrawal:
A Portable Optimization Engine for Accelerating Irregular Data-Traversal Applications on SIMD Architectures. ACM Trans. Archit. Code Optim. 11(2): 16:1-16:31 (2014) - [j29]Mai Zheng, Vignesh T. Ravi, Feng Qin, Gagan Agrawal:
GMRace: Detecting Data Races in GPU Programs via a Low-Overhead Scheme. IEEE Trans. Parallel Distributed Syst. 25(1): 104-115 (2014) - [c203]Tekin Bicer, Jian Yin, Gagan Agrawal:
Improving I/O Throughput of Scientific Applications Using Transparent Parallel Compression. CCGRID 2014: 1-10 - [c202]Rajkumar Kettimuthu, Gayane Vardoyan, Gagan Agrawal, P. Sadayappan:
Modeling and Optimizing Large-Scale Wide-Area Data Transfers. CCGRID 2014: 196-205 - [c201]Mücahid Kutlu, Gagan Agrawal:
Cluster-Based SNP Calling on Large-Scale Genome Sequencing Data. CCGRID 2014: 455-464 - [c200]Yu Su, Gagan Agrawal, Jonathan Woodring, Ayan Biswas, Han-Wei Shen:
Supporting correlation analysis on scientific datasets in parallel and distributed settings. HPDC 2014: 191-202 - [c199]Bin Ren, Nishkam Ravi, Yi Yang, Min Feng, Gagan Agrawal, Srimat T. Chakradhar:
Automating and optimizing data transfers for many-core coprocessors. ICS 2014: 177 - [c198]Xin Huo, Bin Ren, Gagan Agrawal:
A programming system for xeon phis with runtime SIMD parallelization. ICS 2014: 283-292 - [c197]Linchuan Chen, Xin Huo, Gagan Agrawal:
Scheduling Methods for Accelerating Applications on Architectures with Heterogeneous Cores. IPDPS Workshops 2014: 48-57 - [c196]Mücahid Kutlu, Gagan Agrawal:
PAGE: A Framework for Easy PArallelization of GEnomic Applications. IPDPS 2014: 72-81 - [c195]Yi Wang, Gagan Agrawal, Hatice Gulcin Ozer, Kun Huang:
Removing Sequential Bottlenecks in Analysis of Next-Generation Sequencing Data. IPDPS Workshops 2014: 508-517 - [c194]Mehmet Can Kurt, Sriram Krishnamoorthy, Kunal Agrawal, Gagan Agrawal:
Fault-Tolerant Dynamic Task Graph Scheduling. SC 2014: 719-730 - [c193]Mehmet Can Kurt, Gagan Agrawal:
DISC: A Domain-Interaction Based Programming Model with Support for Heterogeneous Execution. SC 2014: 869-880 - [c192]Yi Wang, Arnab Nandi, Gagan Agrawal:
SAGA: array storage as a DB with support for structural aggregations. SSDBM 2014: 9:1-9:12 - [p2]Victor E. Lee, Ruoming Jin, Gagan Agrawal:
Frequent Pattern Mining in Data Streams. Frequent Pattern Mining 2014: 199-224 - 2013
- [j28]Wenjing Ma, Sriram Krishnamoorthy, Oreste Villa, Karol Kowalski, Gagan Agrawal:
Optimizing tensor contraction expressions for hybrid CPU-GPU execution. Clust. Comput. 16(1): 131-155 (2013) - [j27]Vignesh T. Ravi, Michela Becchi, Wei Jiang, Gagan Agrawal, Srimat T. Chakradhar:
Scheduling concurrent applications on a cluster of CPU-GPU nodes. Future Gener. Comput. Syst. 29(8): 2262-2271 (2013) - [j26]David Chiu, Gagan Agrawal:
Cost and Accuracy Aware Scientific Workflow Composition for Service-Oriented Environments. IEEE Trans. Serv. Comput. 6(4): 470-483 (2013) - [c191]Yi Wang, Yu Su, Gagan Agrawal:
Supporting a Light-Weight Data Management Layer over HDF5. CCGRID 2013: 335-342 - [c190]Bin Ren, Gagan Agrawal, James R. Larus, Todd Mytkowicz, Tomi Poutanen, Wolfram Schulte:
SIMD parallelization of applications that traverse irregular data structures. CGO 2013: 20:1-20:10 - [c189]Yu Su, Gagan Agrawal, Jonathan Woodring, Kary L. Myers, Joanne Wendelberger, James P. Ahrens:
Taming massive distributed datasets: data sampling using bitmap indices. HPDC 2013: 13-24 - [c188]Xin Huo, Sriram Krishnamoorthy, Gagan Agrawal:
Efficient scheduling of recursive control flow on GPUs. ICS 2013: 409-420 - [c187]Tekin Bicer, Jian Yin, David Chiu, Gagan Agrawal, Karen Schuchardt:
Integrating Online Compression to Accelerate Large-Scale Data Analytics Applications. IPDPS 2013: 1205-1216 - [c186]Tekin Bicer, Gagan Agrawal:
A Compression Framework for Multidimensional Scientific Datasets. IPDPS Workshops 2013: 2250-2253 - [c185]Yu Su, Yi Wang, Gagan Agrawal, Rajkumar Kettimuthu:
SDQuery DSI: integrating data management support with a wide area data transfer protocol. SC 2013: 47:1-47:12 - 2012
- [j25]Vignesh T. Ravi, Wenjing Ma, David Chiu, Gagan Agrawal:
Compiler and runtime support for enabling reduction computations on heterogeneous systems. Concurr. Comput. Pract. Exp. 24(5): 463-480 (2012) - [j24]Tantan Liu, Fan Wang, Gagan Agrawal:
Stratified sampling for data mining on the deep web. Frontiers Comput. Sci. 6(2): 179-196 (2012) - [j23]Qian Zhu, Gagan Agrawal:
Resource Provisioning with Budget Constraints for Adaptive Applications in Cloud Environments. IEEE Trans. Serv. Comput. 5(4): 497-511 (2012) - [c184]Bin Ren, Gagan Agrawal, James R. Larus, Todd Mytkowicz, Tomi Poutanen, Wolfram Schulte:
Fine-grained parallel traversals of irregular data structures. PACT 2012: 461-462 - [c183]Vignesh T. Ravi, Michela Becchi, Wei Jiang, Gagan Agrawal, Srimat T. Chakradhar:
Scheduling Concurrent Applications on a Cluster of CPU-GPU Nodes. CCGRID 2012: 140-147 - [c182]Yu Su, Gagan Agrawal:
Supporting User-Defined Subsetting and Aggregation over Parallel NetCDF Datasets. CCGRID 2012: 212-219 - [c181]Yi Wang, Wei Jiang, Gagan Agrawal:
SciMATE: A Novel MapReduce-Like Framework for Multiple Scientific Data Formats. CCGRID 2012: 443-450 - [c180]Tekin Bicer, David Chiu, Gagan Agrawal:
Time and Cost Sensitive Data-Intensive Computing on Hybrid Clouds. CCGRID 2012: 636-643 - [c179]Wenjing Ma, Sriram Krishnamoorthy, Gagan Agrawal:
Parameterized micro-benchmarking: an auto-tuning approach for complex applications. Conf. Computing Frontiers 2012: 213-222 - [c178]Mehmet Can Kurt, Gagan Agrawal:
A fault-tolerant environment for large-scale query processing. HiPC 2012: 1-10 - [c177]Mücahid Kutlu, Gagan Agrawal, Oguz Kurt:
Fault tolerant parallel data-intensive algorithms. HiPC 2012: 1-10 - [c176]Mai Zheng, Vignesh T. Ravi, Wenjing Ma, Feng Qin, Gagan Agrawal:
GMProf: A low-overhead, fine-grained profiling approach for GPU programs. HiPC 2012: 1-10 - [c175]Mücahid Kutlu, Gagan Agrawal, Oguz Kurt:
Fault tolerant parallel data-intensive algorithms. HPDC 2012: 133-134 - [c174]Linchuan Chen, Gagan Agrawal:
Optimizing MapReduce for GPUs with effective shared memory usage. HPDC 2012: 199-210 - [c173]Yu Su, Gagan Agrawal, Jonathan Woodring:
Indexing and Parallel Query Processing Support for Visualizing Climate Datasets. ICPP 2012: 249-258 - [c172]Wei Jiang, Gagan Agrawal:
MATE-CG: A Map Reduce-Like Framework for Accelerating Data-Intensive Computations on Heterogeneous Clusters. IPDPS 2012: 644-655 - [c171]Tantan Liu, Gagan Agrawal:
Stratified k-means clustering over a deep web data source. KDD 2012: 1113-1121 - [c170]Linchuan Chen, Xin Huo, Gagan Agrawal:
Accelerating MapReduce on a coupled CPU-GPU architecture. SC 2012: 25 - [c169]Vignesh T. Ravi, Michela Becchi, Gagan Agrawal, Srimat T. Chakradhar:
ValuePack: value-based scheduling framework for CPU-GPU clusters. SC 2012: 53 - [c168]Gagan Agrawal, Yu Su:
Light-Weight Data Management Solutions for Visualization and Dissemination of Massive Scientific Datasets - Position Paper. SC Companion 2012: 1296-1300 - [c167]Tantan Liu, Gagan Agrawal:
Stratification Based Hierarchical Clustering Over a Deep Web Data Source. SDM 2012: 70-81 - 2011
- [j22]David Chiu, Travis Hall, Farhana Kabir, Apeksha Shetty, Gagan Agrawal:
Analyzing Costs and Optimizations for an Elastic Key-Value Store on Amazon Web Services. Int. J. Next Gener. Comput. 2(2) (2011) - [c166]Bin Ren, Gagan Agrawal:
Compiling Dynamic Data Structures in Python to Enable the Use of Multi-core and Many-core Libraries. PACT 2011: 68-77 - [c165]Wenjing Ma, Sriram Krishnamoorthy, Gagan Agrawal:
Parameterized Micro-benchmarking: An Auto-tuning Approach for Complex Applications. PACT 2011: 181-182 - [c164]Wenjing Ma, Sriram Krishnamoorthy, Gagan Agrawal:
Practical Loop Transformations for Tensor Contraction Expressions on Multi-level Memory Hierarchies. CC 2011: 266-285 - [c163]David Chiu, Apeksha Shetty, Gagan Agrawal:
Evaluating and Optimizing Indexing Schemes for a Cloud-Based Elastic Key-Value Store. CCGRID 2011: 362-371 - [c162]Wei Jiang, Gagan Agrawal:
Ex-MATE: Data Intensive Computing with Large Reduction Objects and Its Application to Graph Mining. CCGRID 2011: 475-484 - [c161]Fan Wang, Gagan Agrawal:
Effective stratification for low selectivity queries on deep web data sources. CIKM 2011: 1455-1464 - [c160]Tekin Bicer, David Chiu, Gagan Agrawal:
A Framework for Data-Intensive Computing with Cloud Bursting. CLUSTER 2011: 169-177 - [c159]Ashish Nagavaram, Gagan Agrawal, Michael A. Freitas, Kelly H. Telu, Gaurang Mehta, Rajiv Mayani, Ewa Deelman:
A Cloud-based Dynamic Workflow for Mass Spectrometry Data Analysis. eScience 2011: 47-54 - [c158]Fan Wang, Gagan Agrawal:
Effective and efficient sampling methods for deep web aggregation queries. EDBT 2011: 425-436 - [c157]Aarthi Raveendran, Tekin Bicer, Gagan Agrawal:
An Autonomic Framework for Time and Cost Driven Execution of MPI Programs on Cloud Environments. GRID 2011: 218-219 - [c156]Xin Huo, Vignesh T. Ravi, Gagan Agrawal:
Porting irregular reductions on heterogeneous CPU-GPU configurations. HiPC 2011: 1-10 - [c155]Vignesh T. Ravi, Gagan Agrawal:
A dynamic scheduling framework for emerging heterogeneous systems. HiPC 2011: 1-10 - [c154]Vignesh T. Ravi, Michela Becchi, Gagan Agrawal, Srimat T. Chakradhar:
Supporting GPU sharing in cloud environments with a transparent runtime consolidation framework. HPDC 2011: 217-228 - [c153]Fan Wang, Gagan Agrawal:
Answering Cross-Source Keyword Queries over Deep Web Data Sources. IC3 2011: 475-490 - [c152]Tantan Liu, Gagan Agrawal:
Active learning based frequent itemset mining over the deep web. ICDE 2011: 219-230 - [c151]Xin Huo, Vignesh T. Ravi, Wenjing Ma, Gagan Agrawal:
An execution strategy and optimized runtime support for parallelizing irregular reductions on modern GPUs. ICS 2011: 2-11 - [c150]Fan Wang, Gagan Agrawal:
Answering complex structured queries over the deep web. IDEAS 2011: 115-123 - [c149]David Chiu, Travis Hall, Farhana Kabir, Gagan Agrawal:
An approach towards automatic workflow composition through information retrieval. IDEAS 2011: 170-178 - [c148]Aarthi Raveendran, Tekin Bicer, Gagan Agrawal:
A Framework for Elastic Execution of Existing MPI Programs. IPDPS Workshops 2011: 940-947 - [c147]Bin Ren, Gagan Agrawal, Bradford L. Chamberlain, Steven J. Deitz:
Translating Chapel to Use FREERIDE: A Case Study in Using an HPC Language for Data-Intensive Computing. IPDPS Workshops 2011: 1242-1249 - [c146]Mai Zheng, Vignesh T. Ravi, Feng Qin, Gagan Agrawal:
GRace: a low-overhead mechanism for detecting data races in GPU programs. PPoPP 2011: 135-146 - [c145]Tekin Bicer, David Chiu, Gagan Agrawal:
Poster: a framework for data-intensive computing with cloud bursting. SC Companion 2011: 5-6 - [c144]Tekin Bicer, David Chiu, Gagan Agrawal:
MATE-EC2: a middleware for processing data with AWS. MTAGS@SC 2011: 59-68 - [c143]David Chiu, Travis Hall, Farhana Kabir, Gagan Agrawal:
Keyword Search Support for Automating Scientific Workflow Composition. SSDBM 2011: 571-572 - 2010
- [j21]Qian Zhu, Gagan Agrawal:
Supporting fault-tolerance for time-critical events in distributed environments. Sci. Program. 18(1): 51-76 (2010) - [c142]Wenjing Ma, Gagan Agrawal:
An integer programming framework for optimizing shared memory use on GPUs. PACT 2010: 553-554 - [c141]Fan Wang, Gagan Agrawal:
A Self-Healing Approach for a Domain-Specific Deep Web Search Tool. BIBE 2010: 20-25 - [c140]Tantan Liu, Fan Wang, Gagan Agrawal:
Instance Discovery and Schema Matching with Applications to Biological Deep Web Data Integration. BIBE 2010: 304-305 - [c139]Wei Jiang, Vignesh T. Ravi, Gagan Agrawal:
A Map-Reduce System with an Alternate API for Multi-core Environments. CCGRID 2010: 84-93 - [c138]Smita Vijayakumar, Qian Zhu, Gagan Agrawal:
Dynamic Resource Provisioning for Data Streaming Applications in a Cloud Environment. CloudCom 2010: 441-448 - [c137]Fan Wang, Gagan Agrawal:
Query Reuse Based Query Planning for Searches over the Deep Web. DEXA (2) 2010: 64-79 - [c136]Tantan Liu, Fan Wang, Gagan Agrawal:
Instance Discovery and Schema Matching with Applications to Biological Deep Web Data Integration. DILS 2010: 148-163 - [c135]David Chiu, Gagan Agrawal:
Evaluating caching and storage options on the Amazon Web Services Cloud. GRID 2010: 17-24 - [c134]Smita Vijayakumar, Qian Zhu, Gagan Agrawal:
Automated and dynamic application accuracy management and resource provisioning in a cloud environment. GRID 2010: 33-40 - [c133]Xin Huo, Vignesh T. Ravi, Wenjing Ma, Gagan Agrawal:
Approaches for parallelizing reductions on modern GPUs. HiPC 2010: 1-10 - [c132]Wenjing Ma, Gagan Agrawal:
An integer programming framework for optimizing shared memory use on GPUs. HiPC 2010: 1-10 - [c131]Qian Zhu, Gagan Agrawal:
Resource provisioning with budget constraints for adaptive applications in cloud environments. HPDC 2010: 304-307 - [c130]Tantan Liu, Fan Wang, Jiedan Zhu, Gagan Agrawal:
Differential Analysis on Deep Web Data Sources. ICDM Workshops 2010: 33-40 - [c129]Venkatram Ramanathan, Wenjing Ma, Vignesh T. Ravi, Tantan Liu, Gagan Agrawal:
Parallelizing an Information Theoretic Co-clustering Algorithm Using a Cloud Middleware. ICDM Workshops 2010: 186-193 - [c128]Tantan Liu, Fan Wang, Gagan Agrawal:
Stratified Sampling for Data Mining on the Deep Web. ICDM 2010: 324-333 - [c127]Vignesh T. Ravi, Wenjing Ma, David Chiu, Gagan Agrawal:
Compiler and runtime support for enabling generalized reduction computations on heterogeneous parallel configurations. ICS 2010: 137-146 - [c126]Tekin Bicer, Wei Jiang, Gagan Agrawal:
Supporting fault tolerance in a data-intensive computing middleware. IPDPS 2010: 1-12 - [c125]Wenjing Ma, Gagan Agrawal:
AUTO-GC: Automatic translation of data mining applications to GPU clusters. IPDPS Workshops 2010: 1-8 - [c124]David Chiu, Apeksha Shetty, Gagan Agrawal:
Elastic Cloud Caches for Accelerating Service-Oriented Computations. SC 2010: 1-11 - [c123]Qian Zhu, Jiedan Zhu, Gagan Agrawal:
Power-Aware Consolidation of Scientific Workflows in Virtualized Environments. SC 2010: 1-12
2000 – 2009
- 2009
- [j20]Qian Zhu, Gagan Agrawal:
An adaptive middleware for supporting time-critical event response. Clust. Comput. 12(1): 87-100 (2009) - [c122]David Chiu, Gagan Agrawal:
Hierarchical Caches for Grid Workflows. CCGRID 2009: 228-235 - [c121]Vignesh T. Ravi, Gagan Agrawal:
Performance Issues in Parallelizing Data-Intensive Applications on a Multi-core Cluster. CCGRID 2009: 308-315 - [c120]Wei Jiang, Vignesh T. Ravi, Gagan Agrawal:
Comparing map-reduce and FREERIDE for data-intensive applications. CLUSTER 2009: 1-10 - [c119]Tantan Liu, Fan Wang, Gagan Agrawal:
Exploiting Parallelism to Accelerate Keyword Search on Deep-Web Sources. DILS 2009: 141-156 - [c118]Fan Wang, Yuan Hong, Wenbin Zhang, Gagan Agrawal:
Personality Based Latent Friendship Mining. DMIN 2009: 427-433 - [c117]Vignesh T. Ravi, Gagan Agrawal:
Integrating and optimizing transactional memory in a data mining middleware. HiPC 2009: 215-224 - [c116]Leonid Glimcher, Vignesh T. Ravi, Gagan Agrawal:
Supporting load balancing for distributed data-intensive applications. HiPC 2009: 235-244 - [c115]Fan Wang, Gagan Agrawal:
Extracting Output Metadata from Scientific Deep Web Data Sources. ICDM 2009: 552-561 - [c114]Wenjing Ma, Gagan Agrawal:
A translation system for enabling data mining applications on GPUs. ICS 2009: 400-409 - [c113]David Chiu, Sagar Deshpande, Gagan Agrawal, Rongxing Li:
A Dynamic Approach toward QoS-Aware Service Workflow Composition. ICWS 2009: 655-662 - [c112]Qian Zhu, Gagan Agrawal:
A resource allocation approach for supporting time-critical applications in grid environments. IPDPS 2009: 1-12 - [c111]Wenjing Ma, Gagan Agrawal:
A compiler and runtime system for enabling data mining applications on gpus. PPoPP 2009: 287-288 - [c110]Qian Zhu, Gagan Agrawal:
Supporting fault-tolerance for time-critical events in distributed environments. SC 2009 - [c109]Fan Wang, Gagan Agrawal:
SEEDEEP: A System for Exploring and Querying Scientific Deep Web Data Sources. SSDBM 2009: 74-82 - [c108]David Chiu, Gagan Agrawal:
Enabling Ad Hoc Queries over Low-Level Scientific Data Sets. SSDBM 2009: 218-236 - 2008
- [j19]Leonid Glimcher, Ruoming Jin, Gagan Agrawal:
Middleware for data mining applications on clusters and grids. J. Parallel Distributed Comput. 68(1): 37-53 (2008) - [j18]Xingquan Zhu, Ruoming Jin, Yuri Breitbart, Gagan Agrawal:
MMIS07, 08: mining multiple information sources workshop report. SIGKDD Explor. 10(2): 61-65 (2008) - [c107]Leonid Glimcher, Gagan Agrawal:
A Middleware for Developing and Deploying Scalable Remote Mining Services. CCGRID 2008: 242-249 - [c106]David Chiu, Sagar Deshpande, Gagan Agrawal, Rongxing Li:
Composing geoinformatics workflows with user preferences. GIS 2008: 55 - [c105]David Chiu, Sagar Deshpande, Gagan Agrawal, Rongxing Li:
Cost and accuracy sensitive dynamic workflow composition over grid environments. GRID 2008: 9-16 - [c104]Qian Zhu, Gagan Agrawal:
An Adaptive Middleware for Supporting Time-Critical Event Response. ICAC 2008: 99-108 - [c103]Qian Zhu, Gagan Agrawal:
Resource Allocation for Distributed Streaming Applications. ICPP 2008: 414-421 - [c102]Liang Chen, Han-Wei Shen, Gagan Agrawal:
Supporting a visualization application on a self-adapting grid middleware. IPDPS 2008: 1-8 - [c101]Xuan Zhang, Gagan Agrawal:
Supporting high performance bioinformatics flat-file data processing using indices. IPDPS 2008: 1-8 - [c100]Qian Zhu, Liang Chen, Gagan Agrawal:
Supporting fault-tolerance in streaming grid applications. IPDPS 2008: 1-12 - [c99]Fan Wang, Gagan Agrawal, Ruoming Jin:
Query Planning for Searching Inter-dependent Deep-Web Databases. SSDBM 2008: 24-41 - [e1]Wu-chi Feng, Yuanyuan Yang, Gagan Agrawal:
37th International Conference on Parallel Processing - Workshops, 8-12 September 2008, Portland, Oregon, USA. IEEE Computer Society 2008, ISBN 978-0-7695-3375-9 [contents] - 2007
- [c98]Fan Wang, Gagan Agrawal, Ruoming Jin, Helen Piontkivska:
SNPMiner: A Domain-Specific Deep Web Mining Tool. BIBE 2007: 192-199 - [c97]Fan Wang, Ruoming Jin, Gagan Agrawal, Helen Piontkivska:
Graph and Topological Structure Mining on Scientific Articles. BIBE 2007: 1318-1322 - [c96]Li Weng, Ümit V. Çatalyürek, Tahsin M. Kurç, Gagan Agrawal, Joel H. Saltz:
Optimizing multiple queries on scientific datasets with partial replicas. GRID 2007: 259-266 - [c95]Leonid Glimcher, Gagan Agrawal:
A Performance Prediction Framework for Grid-Based Data Mining Applications. IPDPS 2007: 1-10 - [c94]Qian Zhu, Liang Chen, Gagan Agrawal:
Supporting fault-tolerance in streaming grid applications. PPoPP 2007: 156-157 - [p1]Ruoming Jin, Gagan Agrawal:
Frequent Pattern Mining in Data Streams. Data Streams - Models and Algorithms 2007: 61-84 - 2006
- [j17]Liang Chen, Gagan Agrawal:
A static resource allocation framework for Grid-based streaming applications. Concurr. Comput. Pract. Exp. 18(6): 653-666 (2006) - [j16]Ruoming Jin, Anjan Goswami, Gagan Agrawal:
Fast and exact out-of-core and distributed k-means clustering. Knowl. Inf. Syst. 10(1): 17-40 (2006) - [c93]Kaushik Sinha, Ruoming Jin, Gagan Agrawal, Helen Piontkivska:
Exploratory Tools for FollowUp Studies to Microarray Experiments. BIBE 2006: 81-85 - [c92]Xuan Zhang, Gagan Agrawal:
A Tool for Supporting Integration Across Multiple FlatFile Datasets. BIBE 2006: 141-148 - [c91]Xuan Zhang, Ruoming Jin, Gagan Agrawal:
Assigning Schema Labels Using Ontology And Hueristics. BIBE 2006: 269-280 - [c90]Qian Zhu, Liang Chen, Gagan Agrawal:
Supporting a Real-Time Distributed Intrusion Detection Application on GATES. Euro-Par 2006: 360-370 - [c89]Gagan Agrawal, Hakan Ferhatosmanoglu, Xutong Niu, Keith W. Bedford, Ron Li:
A Vision for Cyberinfrastructure for Coastal Forecasting and Change Analysis. GSN 2006: 151-174 - [c88]Ruoming Jin, Gagan Agrawal:
Systematic Approach for Optimizing Complex Mining Tasks on Multiple Databases. ICDE 2006: 17 - [c87]Ruoming Jin, Leonid Glimcher, Chris Jermaine, Gagan Agrawal:
New Sampling-Based Estimators for OLAP Queries. ICDE 2006: 18 - [c86]Leonid Glimcher, Ruoming Jin, Gagan Agrawal:
FREERIDE-G: Supporting Applications that Mine Remote. ICPP 2006: 109-118 - [c85]Li Weng, Ümit V. Çatalyürek, Tahsin M. Kurç, Gagan Agrawal, Joel H. Saltz:
Using Space and Attribute Partitioned Partial Replicas for Data Subsetting and Aggregation Queries. ICPP 2006: 271-280 - [c84]Xiaogang Li, Gagan Agrawal:
Parallelizing XQuery In a Cluster Environment. IDEAS 2006: 291-294 - [c83]Liang Chen, Gagan Agrawal:
Supporting self-adaptation in streaming data mining applications. IPDPS 2006 - [c82]Liang Chen, Qian Zhu, Gagan Agrawal:
Grid scheduling and protocols - Supporting dynamic migration in tightly coupled grid applications. SC 2006: 117 - 2005
- [j15]Ruoming Jin, Gagan Agrawal:
A methodology for detailed performance modeling of reduction computations on SMP machines. Perform. Evaluation 60(1-4): 73-105 (2005) - [j14]Ruoming Jin, Ge Yang, Gagan Agrawal:
Shared Memory Parallelization of Data Mining Algorithms: Techniques, Programming Interface, and Performance. IEEE Trans. Knowl. Data Eng. 17(1): 71-89 (2005) - [j13]Ruoming Jin, Karthikeyan Vaidyanathan, Ge Yang, Gagan Agrawal:
Communication and Memory Optimal Parallel Data Cube Construction. IEEE Trans. Parallel Distributed Syst. 16(12): 1105-1119 (2005) - [c81]Swarup Kumar Sahoo, Gagan Agrawal:
Data Centric Transformations on Non-Integer Iteration Spaces. IEEE PACT 2005: 133-142 - [c80]Kaushik Sinha, Xuan Zhang, Ruoming Jin, Gagan Agrawal:
Using Data Mining Techniques to Learn Layouts of Flat-File Biological Datasets. BIBE 2005: 177-184 - [c79]Li Weng, Ümit V. Çatalyürek, Tahsin M. Kurç, Gagan Agrawal, Joel H. Saltz:
Servicing range queries on multidimensional datasets with partial replicas. CCGRID 2005: 726-733 - [c78]Kaushik Sinha, Xuan Zhang, Ruoming Jin, Gagan Agrawal:
Learning Layouts of Biological Datasets Semi-automatically. DILS 2005: 31-45 - [c77]Xuan Zhang, Gagan Agrawal:
Enabling information integration and workflows in a grid environment with automatic wrapper generation. GRID 2005: 156-163 - [c76]Ruoming Jin, Gagan Agrawal:
An Algorithm for In-Core Frequent Itemset Mining on Streaming Data. ICDM 2005: 210-217 - [c75]Wei Du, Gagan Agrawal:
Filter Decomposition for Supporting Coarse-Grained Pipelined Parallelism. ICPP 2005: 539-546 - [c74]Leonid Glimcher, Gagan Agrawal, Sameep Mehta, Ruoming Jin, Raghu Machiraju:
Parallelizing a Defect Detection and Categorization Application. IPDPS 2005 - [c73]Ruoming Jin, Kaushik Sinha, Gagan Agrawal:
A framework to support multiple query optimization for complex mining tasks. MDM@KDD 2005: 23-32 - [c72]Ruoming Jin, Kaushik Sinha, Gagan Agrawal:
Simultaneous optimization of complex mining tasks with a knowledgeable cache. KDD 2005: 600-605 - [c71]Ruoming Jin, Chao Wang, Dmitrii Polshakov, Srinivasan Parthasarathy, Gagan Agrawal:
Discovering frequent topological structures from graph datasets. KDD 2005: 606-611 - [c70]Xiaogang Li, Gagan Agrawal:
Code Transformations for One-Pass Analysis. LCPC 2005: 377-396 - [c69]Xiaogang Li, Gagan Agrawal:
Efficient Evaluation of XQuery over Streaming Data. VLDB 2005: 265-276 - 2004
- [c68]Leonid Glimcher, Gagan Agrawal:
Parallelizing EM Clustering Algorithm on a Cluster of SMPs. Euro-Par 2004: 372-380 - [c67]Li Weng, Gagan Agrawal, Ümit V. Çatalyürek, Tahsin M. Kurç, Sivaramakrishnan Narayanan, Joel H. Saltz:
An Approach for Automatic Data Virtualization. HPDC 2004: 24-33 - [c66]Liang Chen, Kolagatla Reddy, Gagan Agrawal:
GATES: A Grid-Based Middleware for Processing Distributed Data Streams. HPDC 2004: 192-201 - [c65]Liang Chen, Gagan Agrawal:
Self-Adaptation in a Middleware for Processing Data Streams. ICAC 2004: 292-293 - [c64]Anjan Goswami, Ruoming Jin, Gagan Agrawal:
Fast and Exact Out-of-Core K-Means Clustering. ICDM 2004: 83-90 - [c63]Wei Du, Gagan Agrawal:
Packet Size Optimization for Supporting Coarse-Grained Pipelined Parallelism. ICPP 2004: 259-266 - [c62]Ruoming Jin, Karthik Vaidyanathan, Ge Yang, Gagan Agrawal:
Using Tiling to Scale Parallel Data Cube Construction. ICPP 2004: 365-372 - [c61]Leonid Glimcher, Xuan Zhang, Gagan Agrawal:
Scaling and Parallelizing a Scientific Feature Mining Application Using a Cluster Middleware. IPDPS 2004 - [c60]Li Weng, Gagan Agrawal, Ümit V. Çatalyürek, Joel H. Saltz:
Supporting SQL-3 Aggregations on Grid-Based Data Repositories. LCPC 2004: 283-298 - [c59]Swarup Kumar Sahoo, Gagan Agrawal:
Supporting XML Based High-Level Abstractions on HDF5 Datasets: A Case Study in Automatic Data Virtualization. LCPC 2004: 299-318 - [c58]Liang Chen, Gagan Agrawal:
Resource allocation in a middleware for streaming data. Middleware for Grid Computing 2004: 5-10 - [c57]Wei Du, Gagan Agrawal:
Language and Compiler Support for Adaptive Applications. SC 2004: 29 - [c56]Xiaogang Li, Swarup Kumar Sahoo, Gagan Agrawal:
XQuery Perspective: Using XML/XQuery for Scientific Applications and Applying Scientific Compilation Techniques. XIME-P 2004: 25-30 - 2003
- [j12]Ge Yang, Ruoming Jin, Gagan Agrawal:
Implementing data cube construction using a cluster middleware: algorithms, implementation experience, and performance evaluation. Future Gener. Comput. Syst. 19(4): 533-550 (2003) - [c55]Xiaogang Li, Gagan Agrawal:
Using XQuery for Flat-File Based Scientific Datasets. DBPL 2003: 179-194 - [c54]Ruoming Jin, Ge Yang, Gagan Agrawal:
Parallel Data Cube Construction: Algorithms, Theoretical Analysis, and Experimental Evaluation. HiPC 2003: 74-84 - [c53]Ruoming Jin, Ge Yang, Karthik Vaidyanathan, Gagan Agrawal:
Communication and Memory Optimal Parallel Data Cube Construction. ICPP 2003: 573-580 - [c52]Xiaogang Li, Renato Ferreira, Gagan Agrawal:
Compiler support for efficient processing of XML datasets. ICS 2003: 42-52 - [c51]Xiaogang Li, Ruoming Jin, Gagan Agrawal:
A Compilation Framework for Distributed Memory Parallelization of Data Mining Algorithms. IPDPS 2003: 7 - [c50]Ge Yang, Ruoming Jin, Gagan Agrawal:
Impact of Data Distribution, Level of Parallelism, and Communication Frequency on Parallel Data Cube Construction. IPDPS 2003: 66 - [c49]Wei Du, Gagan Agrawal:
Compiler Supported Coarse-Grained Pipelined Parallelism: Why and How. IPDPS 2003: 204 - [c48]Ruoming Jin, Gagan Agrawal:
Efficient decision tree construction on streaming data. KDD 2003: 571-576 - [c47]Xiaogang Li, Gagan Agrawal:
Supporting High-Level Abstractions through XML Technology. LCPC 2003: 127-146 - [c46]Wei Du, Renato Ferreira, Gagan Agrawal:
Compiler Support for Exploiting Coarse-Grained Pipelined Parallelism. SC 2003: 8 - [c45]Tahsin M. Kurç, Feng Lee, Gagan Agrawal, Ümit V. Çatalyürek, Renato Ferreira, Joel H. Saltz:
Optimizing Reduction Computations In a Distributed Environment. SC 2003: 9 - [c44]Ruoming Jin, Gagan Agrawal:
Communication and Memory Efficient Parallel Decision Tree Construction. SDM 2003: 119-129 - 2002
- [j11]Kevin B. Theobald, Rishi Kumar, Gagan Agrawal, Gerd Heber, Ruppa K. Thulasiram, Guang R. Gao:
Implementation and evaluation of a communication intensive application on the EARTH multithreaded system. Concurr. Comput. Pract. Exp. 14(3): 183-201 (2002) - [j10]Renato Ferreira, Gagan Agrawal, Joel H. Saltz:
Data parallel language and compiler support for data intensive applications. Parallel Comput. 28(5): 725-748 (2002) - [c43]Gagan Agrawal, Jinqian Li, Qi Su:
Evaluating a Demand Driven Technique for Call Graph Construction. CC 2002: 29-45 - [c42]Ge Yang, Ruoming Jin, Gagan Agrawal:
Implementing Data Cube Construction using a Cluster Middleware: Algorithms, Implementation Experience, and Performance Evaluation. CCGRID 2002: 84-92 - [c41]Wei Du, Gagan Agrawal:
Developing Distributed Data Mining Implementations for a Grid Environment. CCGRID 2002: 440-441 - [c40]Ruoming Jin, Gagan Agrawal:
Runtime support for parallelizing data mining algorithms. Data Mining and Knowledge Discovery: Theory, Tools, and Technology 2002: 212-223 - [c39]Ruoming Jin, Gagan Agrawal:
Shared Memory Parallelization of Decision Tree Construction Using a General Data Mining Middleware. Euro-Par 2002: 346-354 - [c38]Renato Ferreira, Gagan Agrawal, Joel H. Saltz:
Compiler supported high-level abstractions for sparse disk-resident datasets. ICS 2002: 241-251 - [c37]Ruoming Jin, Gagan Agrawal:
Design and Evaluation of a High-Level Interface for Data Mining. IPDPS 2002 - [c36]Rishi Kumar, Gagan Agrawal, Guang R. Gao:
Compiling Several Classes of Communication Patterns on a Multithreaded Architecture. IPDPS 2002 - [c35]Gary M. Zoppetti, Gagan Agrawal, Rishi Kumar:
Compiler and Runtime Support for Irregular Reductions on a Multithreaded Architecture. IPDPS 2002 - [c34]Xiaogang Li, Ruoming Jin, Gagan Agrawal:
Compiler and Runtime Support for Shared Memory Parallelization of Data Mining Algorithms. LCPC 2002: 265-279 - [c33]Ruoming Jin, Gagan Agrawal:
Shared Memory Paraellization of Data Mining Algorithms: Techniques, Programming Interface, and Performance. SDM 2002: 77-94 - [c32]Ruoming Jin, Gagan Agrawal:
Performance prediction for random write reductions: a case study in modeling shared memory programs. SIGMETRICS 2002: 117-128 - 2001
- [c31]Renato Ferreira, Joel H. Saltz, Gagan Agrawal:
Compiler and Runtime Analysis for Efficient Communication in Data Intensive Applications. IEEE PACT 2001: 231-242 - [c30]Gary M. Zoppetti, Gagan Agrawal, Rishi Kumar:
Impact of Data Distribution on Performance of Irregular Reductions on Multithreaded Architectures. HPCN Europe 2001: 483-492 - [c29]Ruoming Jin, Gagan Agrawal:
An efficient association mining implementation on clusters of SMP. IPDPS 2001: 156 - [c28]Gagan Agrawal, Ruoming Jin, Xiaogang Li:
Compiler and Middleware Support for Scalable Data Mining. LCPC 2001: 33-51 - [c27]Gagan Agrawal, Liang Guo:
Evaluating explicitly context-sensitive program slicing. PASTE 2001: 6-12 - [c26]Gary M. Zoppetti, Gagan Agrawal:
An Execution Strategy for Irregular Reductions on Multithreaded Architectures. PP 2001 - [c25]Ruoming Jin, Gagan Agrawal:
A Middleware for Developing Parallel Data Mining Applications. SDM 2001: 1-18 - 2000
- [j9]Dixie Hisley, Gagan Agrawal, Punyam Satya-narayana, Lori L. Pollock:
Porting and performance evaluation of irregular codes using OpenMP. Concurr. Pract. Exp. 12(12): 1241-1259 (2000) - [c24]Gagan Agrawal:
Demand-Driven Construction of Call Graphs. CC 2000: 125-140 - [c23]Kevin B. Theobald, Rishi Kumar, Gagan Agrawal, Gerd Heber, Ruppa K. Thulasiram, Guang R. Gao:
Developing a Communication Intensive Application on the EARTH Multithreaded Architecture (Distinguished Paper). Euro-Par 2000: 625-637 - [c22]Renato Ferreira, Gagan Agrawal, Joel H. Saltz:
Compiling object-oriented data intensive applications. ICS 2000: 11-21 - [c21]Gary M. Zoppetti, Gagan Agrawal, Lori L. Pollock, José Nelson Amaral, Xinan Tang, Guang R. Gao:
Automatic compiler techniques for thread coarsening for multithreaded architectures. ICS 2000: 306-315 - [c20]Renato Ferreira, Gagan Agrawal, Ruoming Jin, Joel H. Saltz:
Compiling Data Intensive Applications with Spatial Coordinates. LCPC 2000: 339-354 - [c19]Gagan Agrawal, Renato Ferreira, Ruoming Jin, Joel H. Saltz:
High Level Programming Methodologies for Data Intensive Computations. LCR 2000: 32-43 - [c18]Kevin B. Theobald, Gagan Agrawal, Rishi Kumar, Gerd Heber, Guang R. Gao, Paul Stodghill, Keshav Pingali:
Landing CG on EARTH: A Case Study of Fine-Grained Multithreading on an Evolutionary Path. SC 2000: 4
1990 – 1999
- 1999
- [j8]Gagan Agrawal:
Data Distribution Analysis for Irregular and Adaptive Codes. Parallel Process. Lett. 9(1): 135-146 (1999) - [j7]Gagan Agrawal, Shyamala Murthy, Chandrashekar Garud:
A Novel Program Representation for Interprocedural Analysis. ACM SIGPLAN Notices 34(4): 70-76 (1999) - [j6]Gagan Agrawal:
A General Interprocedural Framework for Placement of Split-Phase Large Latency Operations. IEEE Trans. Parallel Distributed Syst. 10(4): 394-413 (1999) - [c17]Gagan Agrawal:
Advanced Communication Optimaizations for Data-Parallel Programs. HPCN Europe 1999: 1139-1142 - [c16]Gagan Agrawal:
Simultaneous Demand-Driven Data-Flow and Call Graph Analysis. ICSM 1999: 453-462 - [c15]Gary M. Zoppetti, Gagan Agrawal, Lori L. Pollock:
Thresholding for Work Distribution of Recursive, Multithreaded Functions. LCPC 1999: 485-489 - 1998
- [j5]Gagan Agrawal:
Interprocedural Partial Redundancy Elimination With Application to Distributed Memory Compilation. IEEE Trans. Parallel Distributed Syst. 9(7): 609-625 (1998) - [c14]Gagan Agrawal:
Automatic Data Partitioning for Irregular and Adaptive Applications. ICPP 1998: 587-594 - [c13]Gagan Agrawal:
I/O Granularity Transformations. LCPC 1998: 68-82 - [c12]Dixie Hisley, Gagan Agrawal, Lori L. Pollock:
Evaluating the Effectiveness of a Parallelizing Compiler. LCR 1998: 195-204 - 1997
- [j4]Joel H. Saltz, Gagan Agrawal, Chialin Chang, Raja Das, Guy Edjlali, Paul Havlak, Yuan-Shin Hwang, Bongki Moon, Ravi Ponnusamy, Shamik D. Sharma, Alan Sussman, Mustafa Uysal:
Programming Irregular Applications: Runtime Support, Compilation and Tools. Adv. Comput. 45: 105-153 (1997) - [j3]Gagan Agrawal, Joel H. Saltz:
Interprocedural Data Flow Based Optimizations for Distributed Memory Compilation. Softw. Pract. Exp. 27(5): 519-545 (1997) - 1996
- [c11]Gagan Agrawal, Anurag Acharya, Joel H. Saltz:
An Interprocedural Framework for Placement of Asynchronous I/O Operations. International Conference on Supercomputing 1996: 358-365 - 1995
- [j2]Gagan Agrawal, Pankaj Jalote:
Coding-Based Replication Schemes for Distributed Systems. IEEE Trans. Parallel Distributed Syst. 6(3): 240-251 (1995) - [j1]Gagan Agrawal, Alan Sussman, Joel H. Saltz:
An Integrated Runtime and Compile-Time Approach for Parallelizing Structured and Block Structured Applications. IEEE Trans. Parallel Distributed Syst. 6(7): 747-754 (1995) - [c10]Guy Edjlali, Gagan Agrawal, Alan Sussman, Joel H. Saltz:
Data parallel programming in an adaptive environment. IPPS 1995: 827-832 - [c9]Gagan Agrawal, Joel H. Saltz:
Interprocedural Data Flow Based Optimizations for Compilation of Irregular Problems. LCPC 1995: 465-479 - [c8]Gagan Agrawal, Guy Edjlali, Alan Sussman, Jim Humphries, Joel H. Saltz:
Runtime Support for Programming in Adaptive Parallel Environments. LCR 1995: 241-252 - [c7]Gagan Agrawal, Joel H. Saltz, Raja Das:
Interprocedural Partial Redundancy Elimination and its Application to Distributed Memory Compilation. PLDI 1995: 258-269 - [c6]Gagan Agrawal, Joel H. Saltz:
Interprocedural Compilation of Irregular Applications for Distributed Memory Machines. SC 1995: 48 - 1994
- [c5]Gagan Agrawal, Joel H. Saltz:
Interprocedural Communication Optimizations for Distributed Memory Compilation. LCPC 1994: 283-299 - 1993
- [c4]Gagan Agrawal, Alan Sussman, Joel H. Saltz:
Compiler and runtime support for structured and block structured applications. SC 1993: 578-587 - 1992
- [c3]Gagan Agrawal, Pankaj Jalote:
An Efficient Protocol for Voting In Distributed Systems. ICDCS 1992: 640-647 - [c2]Pankaj Jalote, Gagan Agrawal:
Using Coding to Support Data Resiliency in Distributed Systems. ICDE 1992: 192-199 - [c1]Gagan Agrawal:
Availability of Coding Based Replication Schemes. SRDS 1992: 103-110
Coauthor Index
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