66 citations · 139 across the 8 of their papers we have counts for
9 papers
HPX Smart Executors
Zahra Khatami, Lukas Troska, Hartmut Kaiser +2
The performance of many parallel applications depends on loop-level parallelism. However, manually parallelizing all loops may result in degrading parallel performance, as some of…
Automated Tiling of Unstructured Mesh Computations with Application to Seismological Modelling
Fabio Luporini, Michael Lange, Christian T. Jacobs +3
Sparse tiling is a technique to fuse loops that access common data, thus increasing data locality. Unlike traditional loop fusion or blocking, the loops may have different iteratio…
Redesigning OP2 Compiler to Use HPX Runtime Asynchronous Techniques
Zahra Khatami, Hartmut Kaiser, J. Ramanujam
Maximizing parallelism level in applications can be achieved by minimizing overheads due to load imbalances and waiting time due to memory latencies. Compiler optimization is one o…
A Load-Balanced Parallel and Distributed Sorting Algorithm Implemented with PGX.D
Zahra Khatami, Sungpack Hong, Jinsoo Lee +4
Sorting has been one of the most challenging studied problems in different scientific researches. Although many techniques and algorithms have been proposed on the theory of having…
COFFEE: an Optimizing Compiler for Finite Element Local Assembly
Fabio Luporini, Ana Lucia Varbanescu, Florian Rathgeber +4
The numerical solution of partial differential equations using the finite element method is one of the key applications of high performance computing. Local assembly is its charact…
On Characterizing the Data Movement Complexity of Computational DAGs for Parallel Execution
Venmugil Elango, Fabrice Rastello, Louis-Noël Pouchet +2
Technology trends are making the cost of data movement increasingly dominant, both in terms of energy and time, over the cost of performing arithmetic operations in computer system…