Dynamic DAG scheduling under memory constraints for shared-memory platforms,” Int. J. of Networking and Computing, vol. 11, no. 1, pp. 27-49, 2021.“
Revisiting Dynamic DAG Scheduling under Memory Constraints for Shared-Memory Platforms,” 22nd Workshop on Advances in Parallel and Distributed Computational Models (APDCM 2020), New Orleans, LA, IEEE Computer Society Press, May 2020.“
Taking Advantage of Hybrid Systems for Sparse Direct Solvers via Task-Based Runtimes,” 23rd International Heterogeneity in Computing Workshop, IPDPS 2014, Phoenix, AZ, IEEE, May 2014.“
A Hybridization Methodology for High-Performance Linear Algebra Software for GPUs,” in GPU Computing Gems, Jade Edition, vol. 2: Elsevier, pp. 473-484, 00 2011.“
Faster, Cheaper, Better - A Hybridization Methodology to Develop Linear Algebra Software for GPUs,” LAPACK Working Note, no. 230, 00 2010.“
QR Factorization on a Multicore Node Enhanced with Multiple GPU Accelerators,” Proceedings of IPDPS 2011, no. ICL-UT-10-04, Anchorage, AK, October 2010.“
Scheduling Cholesky Factorization on Multicore Architectures with GPU Accelerators , Knoxville, TN, 2010 Symposium on Application Accelerators in High-Performance Computing (SAAHPC'10), Poster, July 2010.