Md Abdullah Shahneous Bari https://www.linkedin.com/in/abdullahshahneousbari CONTACT Email: mshahneousba@cs.stonybrook.edu Mobile: (832) 807 4699 OBJECTIVE Obtaining a full-time position to explore High Performance Computing, Power and Energy Optimization, Deep Learning, Cloud and Big Data environments. EDUCATION Stony Brook University Stony Brook, NY PhD student in Computer Science. GPA: 3.83/4.0 September, 2016 - Advisor: Dr. Barbara Chapman University of Houston Houston, TX PhD student in Computer Science. GPA: 3.96/4.0 September, 2013 - May, 2016 Advisor: Dr. Barbara Chapman Bangladesh University of Engineering & Technology (BUET) Bangladesh Bachelor of Science in Computer Science & Engineering. 2007-2012 KNOWLEDGE High Performance Computing, GPU Computing, Resilience, Performance Analysis and BASE Modeling, Power aware computing, Compiler optimization (hands on experience on LLVM and OpenUH (an Open64 compiler)). WORK & Lawrence Livermore National Lab Livermore, CA PROJECT Research Summer Intern May, 2018-August, 2018 EXPERIENCE • Worked on GPU data placement optimization. • Primary focus was on the impact of data placement in GPU performance. • Worked towards a novel metric to measure the data movement cost for different data placement strategies in a GPU. • Technologies used: C/C++, CUDA, CUPTI. AMD Research Austin, TX Research Summer Intern May, 2016-August, 2016 • Worked on collaborative processor performance control. • It allows user to pass performance hints to the processor. • Came up with a novel way to predict processor performance at different frequen- cies. • We have a patent based on my findings. • Technologies used: C/C++, ACPI-specification, Linux kernel programming. Schlumberger Houston, TX Summer Intern May, 2015-August, 2015 • Designed and developed a standalone and automated HDF5 Parser. • It is mainly used to automatically parse the flat text output from fracture simu- lators and save them in a structured HDF5 format. • This piece of software allowed the whole simulation process to be parallelized. • Technologies used: C++, C# & HDF5. Dept. of Computer Science, Stony Brook University Stony Brook, NY Research Assistant September, 2016- present • OpenSHMEM – Working on OpenSHMEM reference implementation. – Primarily focused on implementing Eureka style programming environment for OpenSHMEM. – Working on compiler enhanced resilience techniques for OpenSHMEM • Adaptive Runtime Configuration Selector (ARCS) – Developed a framework named “Adaptive Runtime Configuration Selector (ARCS)” for power aware runtime parameter selection of OpenMP parallel regions. – ARCS can select optimum combination of OpenMP runtime parameters (No. of threads, Scheduling Policy, Chunk Size) for a certain parallel region under a certain power cap. – ARCS is able to improve an application performance upto 40%. – Implemented an API to collect energy measurements for specific OpenMP events of an OpenMP application. – Technologies used: Multithreaded Programming(OpenMP), Energy, Power Measurement and Power Capping of Intel processors(via Intel RAPL inter- face) and Hardware Performance Counter Manipulation(via PAPI). • Programming Competition: Innovative Software for Oil & Gas Company – Developed a software as a part of Ocean Academic Competition, USA 2014 (Arranged by Schlumberger). – It was selected as one of the top 6 projects (out of 117 in whole North America). Samsung Research & Development Institute Bangladesh Dhaka, Bangladesh Software Engineer May.2012-August.2013 • Worked on a natural language processing based project for voice command in Samsung smart TV. Worked on user defined voice commands. PATENT • Md Abdullah Shahneous Bari, Leonardo Piga and Indrani Paul. “Bandwidth- aware multi-frequency performance estimation mechanism”, ID: US10048741B1. PUBLICATION • [Journal] Md Abdullah Shahneous Bari, Abid Malik, Ahmad Qawasmeh and Barbara Chapman, “Performance and Energy Impact of OpenMP Runtime Con- figurations on Power Constrained Systems”, in Sustainable Computing: Infor- matics and Systems, 2019. • Md Abdullah Shahneous Bari, Larisa Stoltzfus, Pei-Hung Lin, Chunhua Liao, Murali Emani and Barbara Chapman. “Is Data Placement Optimization Still Relevant On Newer GPUs?” in The 9th IEEE International Workshop on Perfor- mance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS18) at SC’18, November 2018, Dallas, TX. • [BEST PAPER AWARD] Md Abdullah Shahneous Bari, Abid Malik, Ah- mad Qawasmeh and Barbara Chapman, “A Detailed Analysis of OpenMP Run- time Configurations for Power Constrained Systems”, in The Eighth International Green and Sustainable Computing Conference (IGSC2017), October 2017, Or- lando, FL. • Md Abdullah Shahneous Bari, Nicholas Chaimov, Abid M. Malik, Kevin Huck, Barbara Chapman, Allen Maloney and Osman Sarood. “ARCS: Adaptive Run- time Configuration Selection for Power-Constrained OpenMP Applications” in 2016 IEEE International Conference on Cluster Computing(IEEE CLUSTER 2016), Taiwan. LEADERSHIP • Student Volunteer at SC’18 Dallas, TX SKILLS • Computer Science Graduate Student Association, University of Hous- ton Houston, TX Officer in charge (Seminar and Workshop) January, 2014-May, 2016. AWARDS • Finalist (Top 6 among 117 teams) in Ocean Academic Competition (North Amer- ica), USA 2014 arranged by Schlumberger. • SC student volunteer award • Conference travel award: SC’18, IGSC’17 TECHNICAL Languages & Programming Models: C, C++, OpenMP, OpenSHMEM, Ope- SKILLS nACC, CUDA, MPI Basic knowledge: Hadoop, Spark, Python, C#.NET., Assembly Language, Java, ASP.NET, SQL,. Package and Tools: PAPI, Intel RAPL, GDB, TAU,, LLVM, OpenUH Com- piler Suite, HDF5, PGI Profiling Tool, LaTex. RELATED Language and Compiler, Computer Architecture, Parallel Computing, Shared Memory COURSES Computing, Operating Systems, Networking, Machine Learning, Big Data Analytics, Data Structure, Algorithms.
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