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Haidar, A., Y. Jia, P. Luszczek, S. Tomov, A. YarKhan, and J. Dongarra, “Weighted Dynamic Scheduling with Many Parallelism Grains for Offloading of Numerical Workloads to Multiple Varied Accelerators,” Proceedings of the 6th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA'15), vol. No. 5, Austin, TX, ACM, November 2015.  (347.6 KB)
Haidar, A., A. Abdelfattah, M. Zounon, P. Wu, S. Pranesh, S. Tomov, and J. Dongarra, “The Design of Fast and Energy-Efficient Linear Solvers: On the Potential of Half-Precision Arithmetic and Iterative Refinement Techniques,” International Conference on Computational Science (ICCS 2018), vol. 10860, Wuxi, China, Springer, pp. 586–600, June 2018. DOI: 10.1007/978-3-319-93698-7_45  (487.88 KB)
Haidar, A., H. Ltaeif, A. YarKhan, and J. Dongarra, “Analysis of Dynamically Scheduled Tile Algorithms for Dense Linear Algebra on Multicore Architectures,” University of Tennessee Computer Science Technical Report, UT-CS-11-666, (also Lawn 243), March 2011.  (1.65 MB)
Haidar, A., H. Bayraktar, S. Tomov, J. Dongarra, and N. J. Higham, “Mixed-Precision Iterative Refinement using Tensor Cores on GPUs to Accelerate Solution of Linear Systems,” Proceedings of the Royal Society A, vol. 476, issue 2243, November 2020. DOI: 10.1098/rspa.2020.0110  (2.24 MB)
Haidar, A., C. Cao, J. Dongarra, P. Luszczek, and S. Tomov, “Unified Development for Mixed Multi-GPU and Multi-Coprocessor Environments using a Lightweight Runtime Environment,” IPDPS 2014, Phoenix, AZ, IEEE, May 2014.  (1.51 MB)
Haidar, A., A. YarKhan, C. Cao, P. Luszczek, S. Tomov, and J. Dongarra, “Flexible Linear Algebra Development and Scheduling with Cholesky Factorization,” 17th IEEE International Conference on High Performance Computing and Communications, Newark, NJ, August 2015.  (494.31 KB)
Haidar, A., P. Wu, S. Tomov, and J. Dongarra, “Investigating Half Precision Arithmetic to Accelerate Dense Linear System Solvers,” ScalA17: 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, Denver, CO, ACM.  (766.35 KB)
Haidar, A., S. Tomov, A. Abdelfattah, I. Yamazaki, and J. Dongarra, MAtrix, TEnsor, and Deep-learning Optimized Routines (MATEDOR) , Washington, DC, NSF PI Meeting, Poster, April 2018. DOI: 10.6084/m9.figshare.6174143.v3  (2.4 MB)
Haidar, A., P. Luszczek, J. Kurzak, and J. Dongarra, “An Improved Parallel Singular Value Algorithm and Its Implementation for Multicore Hardware,” Supercomputing 2013, Denver, CO, November 2013.
Haidar, A., J. Kurzak, G. Pichon, and M. Faverge, “ A Data Flow Divide and Conquer Algorithm for Multicore Architecture,” 29th IEEE International Parallel & Distributed Processing Symposium (IPDPS), Hyderabad, India, IEEE, May 2015.  (535.44 KB)
Haidar, A., T. Dong, P. Luszczek, S. Tomov, and J. Dongarra, “Optimization for Performance and Energy for Batched Matrix Computations on GPUs,” 8th Workshop on General Purpose Processing Using GPUs (GPGPU 8), San Francisco, CA, ACM, February 2015. DOI: 10.1145/2716282.2716288  (699.5 KB)
Haidar, A., A. Abdelfattah, M. Zounon, S. Tomov, and J. Dongarra, “A Guide for Achieving High Performance with Very Small Matrices on GPUs: A Case Study of Batched LU and Cholesky Factorizations,” IEEE Transactions on Parallel and Distributed Systems, vol. 29, issue 5, pp. 973–984, May 2018. DOI: 10.1109/TPDS.2017.2783929  (832.92 KB)
Haidar, A., H. Ltaeif, and J. Dongarra, “Parallel Reduction to Condensed Forms for Symmetric Eigenvalue Problems using Aggregated Fine-Grained and Memory-Aware Kernels,” University of Tennessee Computer Science Technical Report, UT-CS-11-677, (also Lawn254), August 2011.  (636.01 KB)
Haidar, A., H. Bayraktar, S. Tomov, J. Dongarra, and N. J. Higham, “Mixed-Precision Solution of Linear Systems Using Accelerator-Based Computing,” Innovative Computing Laboratory Technical Report, no. ICL-UT-20-05: University of Tennessee, May 2020.  (1.03 MB)
Haidar, A., P. Luszczek, S. Tomov, and J. Dongarra, “Heterogeneous Acceleration for Linear Algebra in Mulit-Coprocessor Environments,” VECPAR 2014, Eugene, OR, June 2014.  (276.52 KB)
Haidar, A., T. Dong, S. Tomov, P. Luszczek, and J. Dongarra, “Framework for Batched and GPU-resident Factorization Algorithms to Block Householder Transformations,” ISC High Performance, Frankfurt, Germany, Springer, July 2015.  (778.26 KB)
Haidar, A., H. Jagode, A. YarKhan, P. Vaccaro, S. Tomov, and J. Dongarra, “Power-aware Computing: Measurement, Control, and Performance Analysis for Intel Xeon Phi,” 2017 IEEE High Performance Extreme Computing Conference (HPEC'17), Best Paper Finalist, Waltham, MA, IEEE, September 2017. DOI: 10.1109/HPEC.2017.8091085  (908.84 KB)
Haidar, A., S. Tomov, A. Abdelfattah, M. Zounon, and J. Dongarra, Using GPU FP16 Tensor Cores Arithmetic to Accelerate Mixed-Precision Iterative Refinement Solvers and Reduce Energy Consumption , Frankfurt, Germany, ISC High Performance (ISC18), Best Poster Award, June 2018.  (3.01 MB)
Haidar, A., H. Ltaeif, and J. Dongarra, “Toward High Performance Divide and Conquer Eigensolver for Dense Symmetric Matrices,” SIAM Journal on Scientific Computing (Accepted), July 2012.
Haidar, A., P. Luszczek, and J. Dongarra, “New Algorithm for Computing Eigenvectors of the Symmetric Eigenvalue Problem,” Workshop on Parallel and Distributed Scientific and Engineering Computing, IPDPS 2014 (Best Paper), Phoenix, AZ, IEEE, May 2014. DOI: 10.1109/IPDPSW.2014.130  (2.33 MB)
Haidar, A., A. Abdelfattah, S. Tomov, and J. Dongarra, “Batched Matrix Computations on Hardware Accelerators Based on GPUs,” 2015 SIAM Conference on Applied Linear Algebra (SIAM LA), Atlanta, GA, SIAM, October 2015.  (9.36 MB)
Haidar, A., H. Jagode, P. Vaccaro, A. YarKhan, S. Tomov, and J. Dongarra, “Investigating Power Capping toward Energy-Efficient Scientific Applications,” Concurrency Computation: Practice and Experience, vol. 2018, issue e4485, pp. 1-14, April 2018. DOI: 10.1002/cpe.4485  (1.2 MB)
Haidar, A., L. Giraud, H. Ben-Hadj-Ali, F. Sourbier, S. Operto, and J. Virieux, “3-D parallel frequency-domain visco-acoustic wave modelling based on a hybrid direct/iterative solver,” 73rd EAGE Conference & Exhibition incorporating SPE EUROPEC 2011, Vienna, Austria, 23-26 May, 00 2011.
Haidar, A., A. Abdelfattah, V. Dobrev, I. Karlin, T. Kolev, S. Tomov, and J. Dongarra, Accelerating Tensor Contractions for High-Order FEM on CPUs, GPUs, and KNLs , Gatlinburg, TN, moky Mountains Computational Sciences and Engineering Conference (SMC16), Poster, September 2016.  (4.29 MB)
Haidar, A., R. Solcà, M. Gates, S. Tomov, T. C. Schulthess, and J. Dongarra, “A Novel Hybrid CPU-GPU Generalized Eigensolver for Electronic Structure Calculations Based on Fine Grained Memory Aware Tasks,” International Journal of High Performance Computing Applications, vol. 28, issue 2, pp. 196-209, May 2014. DOI: 10.1177/1094342013502097  (1.74 MB)
Haidar, A., T. Dong, P. Luszczek, S. Tomov, and J. Dongarra, “Batched matrix computations on hardware accelerators based on GPUs,” International Journal of High Performance Computing Applications, February 2015. DOI: 10.1177/1094342014567546  (2.16 MB)
Haidar, A., B. Brock, S. Tomov, M. Guidry, J. Jay Billings, D. Shyles, and J. Dongarra, “Performance Analysis and Acceleration of Explicit Integration for Large Kinetic Networks using Batched GPU Computations,” 2016 IEEE High Performance Extreme Computing Conference (HPEC ‘16), Waltham, MA, IEEE, September 2016.  (480.29 KB)
Haidar, A., S. Tomov, A. Abdelfattah, M. Zounon, and J. Dongarra, “Using GPU FP16 Tensor Cores Arithmetic to Accelerate Mixed-Precision Iterative Refinement Solvers and Reduce Energy Consumption,” ISC High Performance (ISC'18), Best Poster, Frankfurt, Germany, June 2018.  (3.01 MB)
Haidar, A., H. Ltaeif, P. Luszczek, and J. Dongarra, “A Comprehensive Study of Task Coalescing for Selecting Parallelism Granularity in a Two-Stage Bidiagonal Reduction,” IPDPS 2012, Shanghai, China, May 2012.  (480.43 KB)
Haidar, A., J. Dongarra, K. Kabir, M. Gates, P. Luszczek, S. Tomov, and Y. Jia, “HPC Programming on Intel Many-Integrated-Core Hardware with MAGMA Port to Xeon Phi,” Scientific Programming, vol. 23, issue 1, January 2015. DOI: 10.3233/SPR-140404  (553.94 KB)
Haidar, A., P. Luszczek, S. Tomov, and J. Dongarra, “Efficient Eigensolver Algorithms on Accelerator Based Architectures,” 2015 SIAM Conference on Applied Linear Algebra (SIAM LA), Atlanta, GA, SIAM, October 2015.  (6.98 MB)
Haidar, A., A. Abdelfattah, S. Tomov, and J. Dongarra, “High-performance Cholesky Factorization for GPU-only Execution,” Proceedings of the General Purpose GPUs (GPGPU-10), Austin, TX, ACM, February 2017. DOI: 10.1145/3038228.3038237  (872.18 KB)
Haidar, A., H. Ltaeif, and J. Dongarra, “Toward High Performance Divide and Conquer Eigensolver for Dense Symmetric Matrices.,” Submitted to SIAM Journal on Scientific Computing (SISC), 00 2011.
Haidar, A., H. Jagode, A. YarKhan, P. Vaccaro, S. Tomov, and J. Dongarra, Power-Aware HPC on Intel Xeon Phi KNL Processors , Frankfurt, Germany, ISC High Performance (ISC17), Intel Booth Presentation, June 2017.  (5.87 MB)
Haidar, A., S. Tomov, J. Dongarra, R. Solcà, and T. C. Schulthess, “Leading Edge Hybrid Multi-GPU Algorithms for Generalized Eigenproblems in Electronic Structure Calculations,” International Supercomputing Conference (ISC), Lecture Notes in Computer Science, vol. 7905, Leipzig, Germany, Springer Berlin Heidelberg, pp. 67-80, June 2013. DOI: 10.1007/978-3-642-38750-0_6  (2.14 MB)
Haidar, A., P. Luszczek, S. Tomov, and J. Dongarra, “Towards Batched Linear Solvers on Accelerated Hardware Platforms,” 8th Workshop on General Purpose Processing Using GPUs (GPGPU 8) co-located with PPOPP 2015, San Francisco, CA, ACM, February 2015.  (403.74 KB)
Haidar, A., S. Tomov, K. Arturov, M. Guney, S. Story, and J. Dongarra, “LU, QR, and Cholesky Factorizations: Programming Model, Performance Analysis and Optimization Techniques for the Intel Knights Landing Xeon Phi,” IEEE High Performance Extreme Computing Conference (HPEC'16), Waltham, MA, IEEE, September 2016.  (943.23 KB)
Haidar, A., S. Tomov, J. Dongarra, and N. J. Higham, “Harnessing GPU Tensor Cores for Fast FP16 Arithmetic to Speed up Mixed-Precision Iterative Refinement Solvers,” The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), Dallas, TX, IEEE, November 2018. DOI: 10.1109/SC.2018.00050  (642.51 KB)
Haidar, A., H. Ltaeif, and J. Dongarra, “Parallel Reduction to Condensed Forms for Symmetric Eigenvalue Problems using Aggregated Fine-Grained and Memory-Aware Kernels,” Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC11), Seattle, WA, November 2011.  (636.01 KB)
Haidar, A., C. Cao, I. Yamazaki, J. Dongarra, M. Gates, P. Luszczek, and S. Tomov, “Performance and Portability with OpenCL for Throughput-Oriented HPC Workloads Across Accelerators, Coprocessors, and Multicore Processors,” 5th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA '14), New Orleans, LA, IEEE, November 2014. DOI: 10.1109/ScalA.2014.8  (407.5 KB)
Haidar, A., S. Tomov, P. Luszczek, and J. Dongarra, “MAGMA Embedded: Towards a Dense Linear Algebra Library for Energy Efficient Extreme Computing,” 2015 IEEE High Performance Extreme Computing Conference (HPEC ’15), (Best Paper Award), Waltham, MA, IEEE, September 2015.  (678.86 KB)
Haidar, A., K. Kabir, D. Fayad, S. Tomov, and J. Dongarra, “Out of Memory SVD Solver for Big Data,” 2017 IEEE High Performance Extreme Computing Conference (HPEC'17), Waltham, MA, IEEE, September 2017.  (1.33 MB)
Haidar, A., H. Ltaeif, A. YarKhan, and J. Dongarra, “Analysis of Dynamically Scheduled Tile Algorithms for Dense Linear Algebra on Multicore Architectures,” Submitted to Concurrency and Computations: Practice and Experience, November 2010.  (1.65 MB)
Haidar, A., A. Abdelfattah, S. Tomov, and J. Dongarra, Harnessing GPU's Tensor Cores Fast FP16 Arithmetic to Speedup Mixed-Precision Iterative Refinement Solvers and Achieve 74 Gflops/Watt on Nvidia V100 , San Jose, CA, GPU Technology Conference (GTC), Poster, March 2018.  (2.96 MB)
Haidar, A., P. Luszczek, J. Kurzak, and J. Dongarra, “An Improved Parallel Singular Value Algorithm and Its Implementation for Multicore Hardware,” University of Tennessee Computer Science Technical Report (also LAWN 283), no. ut-eecs-13-720: University of Tennessee, October 2013.  (1.23 MB)
Haidar, A., P. Luszczek, S. Tomov, and J. Dongarra, “Batched Matrix Computations on Hardware Accelerators,” EuroMPI/Asia 2015 Workshop, Bordeaux, France, September 2015.  (589.05 KB)