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Publications

Conference Papers

  • T. Nguyen and M. Becchi, “A Transducers-based Programming Framework for Efficient Data Transformation”, in Proc. of the International Conference on Parallel Architectures and Compilation Techniques (PACT 2024)
  • T. Nguyen, H. Rahman, S. Di, M. Becchi, “CAROL: Significantly Improving Fixed-Ratio Compression Framework for Resource-limited Applications”, Proceedings of the 53rd International Conference on Parallel Processing (ICPP 2024)
  • M. Shah, X. Yu, S. Di, M. Becchi, and F. Cappello, “A Portable, Fast, DCT-based Compressor for AI Accelerators”, In Proc. of the 33rd International ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC 2024)
  • R. Neff, M. Eghbali Zarch, M. Minutoli, M. Halappanavar, A. Tumeo, A. Kalyanaraman, M. Becchi, “FuseIM: Fusing Probabilistic Traversals for Influence  Maximization on Exascale Systems”, 38th ACM International Conference on Supercomputing (ICS 2024).
  • SM Ferdous, R. Neff, B. Peng, S. Shuvo, M. Minutoli, S. Mukherjee, K. Kowalski, M. Becchi, M. Halappanavar, “Picasso: Memory-Efficient Graph Coloring Usin Palettes With Applications in Quantum Computing”, 38th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2024)
  • R. Neff, M. Minutoli, A. Tumeo, and M. Becchi. “2023. “High-Level Synthesis of Irregular Applications: A Case Study on Influence Maximization”, Proceedings of the 20th ACM International Conference on Computing Frontiers (CF 2023).
  • M. Eghbali Zarch and M. Becchi, “A Code Transformation to Improve the Efficiency of OpenCL Code on FPGA through Pipes,” Proceedings of the 20th ACM International Conference on Computing Frontiers (CF 2023).
  • M. Shah, X. Yu, S. Di, M. Becchi, and F. Cappello, “Lightweight Huffman Coding for Efficient GPU Compression”, Proceedings of the 37th International Conference on Supercomputing (ICS 2023).
  • J. Ravi, S. Byna, M. Becchi, “In-transit Data Compression on Heterogeneous HPC Systems”, 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2023)
  • M. Shah, X. Yu, S. Di, D. Lykov, Y. Alexeev, M. Becchi, F. Cappello, “GPU-Accelerated Error-Bounded Compression Framework for Quantum Circuit Simulations”, 37th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2023)
  • J. Ravi, S. Byna, Q. Koziol, H. Tang, M. Becchi, “Evaluating Asynchronous Parallel IO on HPC Systems”, 37th IEEE International Parallel and Distributed Processing Symposium (IPDPS 2023)
  • M. Nourian, Tri Nguyen, A. Chien, M. Becchi, “Data Transformation Acceleration using Deterministic Finite-State Transducers”, 2022 IEEE International Conference on Big Data (Big Data 2022) [acceptance rate=19.2%]
  • T. Nguyen and M. Becchi, “A GPU-accelerated Data Transformation Framework Rooted in Pushdown Transducers”, IEEE International Conference on High Performance Computing, Data, and Analytics. (HiPC 2022) [acceptance rate=25%]
  • M. Shah, R. Neff, H. Wu,  M. Minutoli, A. Tumeo, M. Becchi, “Accelerating Random Forest Classification on GPU and FPGA”, Proceedings of the 51st International Conference on Parallel Processing (ICPP 2022) [acceptance rate=27%]
  • M. E. Zarch, R. Neff and M. Becchi, “Exploring Thread Coarsening on FPGA,” 2021 IEEE 28th International Conference on High Performance Computing, Data, and Analytics, December 2021 (HiPC 2021)
  • J. Ravi, T. Nguyen, H. Zhou and M. Becchi, “PILOT: a Runtime System to Manage Multi-tenant GPU Unified Memory Footprint,” 2021 IEEE 28th International Conference on High Performance Computing, Data, and Analytics, December 2021 (HiPC 2021)
  • M. Nourian, M. Eghbali Zarch, and M. Becchi, “Optimizing Complex OpenCL Code for FPGA: A Case Study on Finite Automata Traversal,“ in Proc. of 26th International Conference on Parallel and Distributed Systems (ICPADS 2020), Hong Kong, December 2020. 
  • R. Gu and M. Becchi, “GPU-FPtuner: Mixed-precision Auto-tuning for Floating-point Applications on GPU,” in Proc. of 27th IEEE International Conference on High Performance Computing (HiPC 2020), December 2020.
  • X. Yu, F. Wei, X. Ou , M. Becchi, T. Bicer , D. Yao, “GPU-Based Static Data-Flow Analysis for Fast and Scalable Android App Vetting,” in Proc. of 34th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2020), New Orleans, LA, May 2020.
  • H. Wu and M. Becchi, “Evaluating Thread Coarsening and Low-cost Synchronization on Intel Xeon Phi,” in Proc. of 34th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2020), New Orleans, LA, May 2020.
  • R. Gu, P. Beata and M. Becchi, “A Loop-aware Autotuner for High-Precision Floating-point Applications,” in Proc. of the 2020 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS 2020), Boston, MA, April 2020.
  • A. Can Mert, E. Karabulut, E. Ozturk, E. Savas, M. Becchi, A. Aysu, “A Flexible and Scalable NTT Hardware: Applications from Homomorphically Encrypted Deep Learning to Post-Quantum Cryptography,” in Proc. of the Design, Automation, and Test in Europe Conference (DATE 2020), Grenoble, France, March 2020.
  • R. Gu, P. Beata and M. Becchi, “Characterizing Performance/Accuracy Tradeoffs of High Precision Applications via Auto-tuning,” in Proc. of 2019 IEEE International Symposium on Workload Characterization (IISWC 2019), Orlando, FL, September 2019.
  • R. Gu and M. Becchi, “A Comparative Study of Parallel Programming Frameworks for Distributed GPU Applications,” in Proc. of the 16th ACM International Conference on Computing Frontiers (CF 2019), Alghero, Italy, May 2019.
  • M. Nourian, H. Wu and M. Becchi, “A Compiler Framework for Fixed-Topology Non-Deterministic Finite Automata on SIMD Platforms, “ in Proc. of 24th International Conference on Parallel and Distributed Systems (ICPADS 2018), Singapore, Singapore, December 2018. 
  • H. Wu, J. Ravi and M. Becchi, “Compiling SIMT Programs on Multi- and Many-Core Processors with Wide Vector Units: A Case Study with CUDA,” in Proc. of 25th IEEE International Conference on High Performance Computing (HiPC 2018), Bengaluru, India, December 2018. [acceptance rate=33/151=21.9%]
  • H. Wu, M. Becchi,  “An Analytical Study of Recursive Tree Traversal Patterns on Multi- and Many-core Platforms,” in Proc. of International Conference on Parallel and Distributed Systems (ICPADS 2017), Shenzen, China, December 2017.
  • A. Todd, M. Nourian, M. Becchi, “A Memory-Efficient GPU Method for Hamming and Levenshtein Distance Similarity” in 24th IEEE International Conference on High Performance Computing, Data and Analytics (HiPC 2017), Jaipur, India, December 2017.  [acceptance rate=42/184=23%]
  • S. Surineni, R. Gu, H. Huyen, M. Becchi, “Understanding the Performance-Accuracy Tradeoffs of Floating Point Arithmetic on GPUs,” in Proc. of 2017 IEEE International Symposium on Workload Characterization (IISWC 2017), Seattle, WA, October 2017. [acceptance rate=23/83=28%]
  • M. Nourian, X. Wang, X. Yu, W.-c. Feng, M. Becchi, “Demistifying Automata Processing: GPUs, FPGAs or Micron’s AP?, ” in Proc. of the International Conference in Supercomputing (ICS 2017), Chicago, IL, June 2017. [acceptance rate=28/177=16%]
  • A. Todd, H. Truong, J. Deters, J. Long, G. Conant, M. Becchi, “Parallel Gene Upstream Comparison via Multi-Level Hash Tables on GPU,” in Proc. of the 22nd IEEE International Conference on Parallel and Distributed Systems (ICPADS 2016), Wuhan, China.  [acceptance rate=30%]
  • D. Li, X. Chen, M. Becchi and Z. Zong, “Evaluating the Energy Efficiency of Deep Convolutional Neural Networks on CPUs and GPUs,” in Proc. of the 2016 IEEE International Conference on Sustainable Computing and Communications (SustainCom 2016), Atlanta, GA, October 2016.
  • W. Harrison, I. Graves, A. Procter, M. Becchi, G. Allwein, “A Programming Model for Reconfigurable Computing Based in Functional Concurrency,” in Proc of the 11th International Symposium on Reconfigurable Communication-centric Systems-on-Chip (ReCoSoC 2016), Tallinn, Estonia, June 2016.
  • K. Sajjapongse, R. Gu and M. Becchi, “IVM: A Task-based Shared Memory Programming Model and Runtime System to Enable Load Balancing and Uniform Access to Heterogeneous CPU-GPU Clusters,” In Proc. of the 13th ACM International Conference on Computing Frontiers (CF 2016), Como, Italy, May 2016. [acceptance rate=30/94=32%]
  • H. Wu , D. Li and M. Becchi, “Compiler-Assisted Workload Consolidation For Efficient Dynamic Parallelism on GPU,” in Proc. of the 30th IEEE International Parallel & Distributed Processing Symposium submitted (IPDPS 2016), Chicago, IL, May 2016. [acceptance rate=114/496=23%]
  • I. Roy, A. Srivastava, M. Nourian, M. Becchi and S. Aluru, “High Performance Pattern Matching Using the Automata Processor,” in Proc. of the 30th IEEE International Parallel & Distributed Processing Symposium submitted (IPDPS 2016), Chicago, IL, May 2016. [acceptance rate=114/496=23%]
  • X. Yu, W.-C. Feng, D. Yao, and M. Becchi, “O3FA: A Scalable, Finite Automata-based, Pattern-Matching Engine for Out-of-Order Packet Inspection in IDS,” In Proc. of the 12th ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS 2016), Santa Clara, CA, March 2016. [acceptance rate: 12/58 = 20.7%]

Journal Articles

Workshop Papers, Short Papers & Posters

  • T. Nguyen and M. Becchi, “PDTgcomp: Compilation Framework for Data Transformation Kernels on GPU”, International Conference for High Performance Computing, Networking, Storage, and Analysis – Posters Program (SC 2022) [poster]
  • R. Neff, M. Minutoli, A. Tumeo, M. Halappanavar, M. Becchi, “Exploring FPGA Acceleration of Seed Selection in Influence Maximization”, International Conference for High Performance Computing, Networking, Storage, and Analysis – Posters Program (SC 2022) [poster]
  • M. Shah, X. Yu, S. Di, M. Becchi, F. Cappello, “Exploring FPGA Acceleration of Seed Selection in Influence Maximization”, International Conference for High Performance Computing, Networking, Storage, and Analysis (SC 2022) – ACM SRC Posters Program 2nd price at ACM Student Research Competition [poster and talk]
  • J. Ravi, “Toward Scalable Middleware for Shared HPC Resources”, International Conference for High Performance Computing, Networking, Storage, and Analysis – Doctoral Showcase Program (SC 2022) [poster and talk]
  • R. Neff, M. Minutoli, A. Tumeo and M. Becchi, “FPGA-Accelerated Ripples”: presented at International Conference for High Performance Computing, Networking, Storage and Analysis (SC 21) – poster presentation [poster]
  • M. Nourian, M. Eghbali and M. Becchi, “Porting Finite State Automata Traversal from GPU to FPGA: Exploring the Implementation Space,” International Conference for High Performance, Networking, Storage, and Analysis (SC 2019), Denver, CO, November 2019 [poster]
  • M. Nourian and M. Becchi, “Analysis of Automata Processing Acceleration on Disparate Hardware Technologies,” International Conference for High Performance, Networking, Storage, and Analysis (SC 2019), Doctoral Showcase Program, Denver, CO, November 2019 [poster]
  • R. Gu, P. Beata and M. Becchi, “Floating-point Autotuner for CPU-based Mixed-precision Applications,” International Conference for High Performance
    Computing, Networking, Storage, and Analysis (SC 2018), Dallas, TX, November 2018 [poster]
  • M. Nourian, H. Wu and M. Becchi, “A Compiler Framework for Fixed-topology Non-deterministic Finite Automata on SIMD Platforms,” International Conference for High Performance Computing, Networking, Storage, and Analysis (SC 2018), Dallas, TX, November 2018 [poster]
  • H. Wu, J. Ravi and M. Becchi, “Compiling SIMT Programs on Multi- and Many-core Processors with Wide Vector Units: A Case Study with CUDA,” International Conference for High Performance, Networking, Storage, and Analysis (SC 2018), Dallas, TX, November 2018 [poster]
  • H. Wu, and M. Becchi, “Efficient Deployment of Irregular Computations on Multi- and Many-Core Architectures,” International Conference for High Performance, Networking, Storage, and Analysis (SC 2018), Doctoral Showcase Program, Dallas, TX, November 2018 
  • J. Ravi, C. Laplante and M. Becchi, “Accelerating Microscope Data Analysis Using Parallel Computing,” International Conference for High Performance, Networking, Storage, and Analysis (SC 2018), ACM Student Research Competition, Dallas, TX, November 2018 (finalist) [poster]
  • D. Li and M. Becchi, ”Facilitating Irregular Applications on Many-core Processors,” International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2015), Doctoral Showcase Program, New Orleans, LA, November 2015. 
  • M. Butler and M. Becchi, “Improving Application Concurrency on GPUs by Managing Implicit and Explicit Synchronizations, “ in International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2015), ACM Student Research Competition, November 2015 (finalist). [poster and talk]
  • D. Chapp, T. Johnston, M. Becchi, and M. Taufer, Numerical Reproducibility Challenges on Extreme Scale Multi-Threading GPUs. GPU Technology Conference (GTC 2015), San Jose, CA, March 2015. (talk).
  • D. Li and M. Becchi, Designing Code Variants for Applications with Nested Parallelism on GPUs. GPU Technology Conference (GTC 2015), San Jose, CA, March 2015. (poster).
  • D. Li, H. Wu, and M. Becchi, Exploiting Dynamic Parallelism to Efficiently Support Irregular Nested Loops on GPUs. In Proc. of the International Workshop on Code Optimisation for Multi and Many Cores (COSMIC 2015), San Francisco, CA, February 2015. (paper).
  • K. Sajjapongse and M. Becchi, Hierarchical Scheduling Frameworks for Heterogeneous Clusters with GPUs. In Proc. of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2014) – Doctoral Showcase Program, New Orleans, LA, November 2014. (poster and talk).
  • T. Agarwal and M. Becchi, Design of a Hybrid MPI-CUDA Benchmark Suite for CPU-GPU Clusters. In Proc of the 23rd International Conference on Parallel Architectures and Compilation Techniques (PACT 2014), Edmonton, Canada, August 2014. Winner of ACM Student Research Competition
  • K. Sajjapongse and M. Becchi, Design of a Virtualization Framework to Enable GPU Sharing in Cluster Environments. GPU Technology Conference (GTC 2014), San Jose, CA, March 2014. (talk).
  • A. Procter, W. Harrison, I. Graves, M. Becchi and G. Allwein, Semantics-directed Machine Architecture in ReWire. In Proc. of the 2013 International Conference on Field Programmable Technology (ICFPT 2013), Kyoto, Japan, December 2013. (short paper)
  • M. Becchi, K. Sajjapongse, I. Graves, A. Procter, V. Ravi, S. Chakradhar, Node-Level Runtime System to Support Multi-tenancy in Clusters with GPUs. GPU Technology Conference (GTC 2013), San Jose, CA, March 2013. (poster).
  • X. Yu and M. Becchi, Exploring Different Automata Representations for Efficient Regular Expression Matching on GPU. In Proc. of the 18th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPOPP 2013), Shenzhen, China, February 2013 (poster).
  • D. Li and M. Becchi, Multiple Pairwise Sequence Alignments with the Needleman-Wunsch Algorithm on GPU. In Proc. of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2012), Salt Lake City, UT, November 2012 (poster).
  • D. Li and M. Becchi, Software Support for Regular and Irregular Applications in Parallel Computing. In Proc. of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2012) – Early Doctoral Showcase Program, Salt Lake City, UT, November 2012 (poster).
  • K. Sajjapongse and M. Becchi, An Efficient Runtime Technology for Many-Core Device Virtualization in Clusters. In Proc. of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC 2012) – Early Doctoral Showcase Program, Salt Lake City, UT, November 2012 (poster).
  • M. Poostchi, K. Palaniappan, F. Bunyak, M. Becchi, G. Seetharaman. Efficient GPU Implementation of the Integral Histogram. In Proc. of the ACCV 2012 Workshop on Developer-Centred Computer Vision (DCCV 2012), Daejeon, Korea, November 2012. (workshop paper)
  • M. Becchi, S. Cadambi and S. T. Chakradhar, Enabling Legacy Applications on Heterogeneous Platforms. In Proc. of the 2nd USENIX Workshop on Hot Topics in Parallelism (HotPar 2010), Berkeley, CA, June 2010. (workshop paper)

Patents