12 citations · 16 across the 5 of their papers we have counts for
5 papers
End-to-end performance of quantum-accelerated large-scale linear algebra workflows
Daiwei Zhu, Miguel Angel Lopez-Ruiz, François-Henry Rouet +5
Solving large-scale sparse linear systems is a challenging computational task due to the introduction of non-zero elements, or "fill-in". The Graph Partitioning Problem (GPP) arise…
Accelerating large-scale linear algebra using variational quantum imaginary time evolution
Willie Aboumrad, Daiwei Zhu, Claudio Girotto +6
The solution of large sparse linear systems via factorization methods such as LU or Cholesky decomposition, can be computationally expensive due to the introduction of non-zero ele…
Callipepla: Stream Centric Instruction Set and Mixed Precision for Accelerating Conjugate Gradient Solver
Linghao Song, Licheng Guo, Suhail Basalama +3
The continued growth in the processing power of FPGAs coupled with high bandwidth memories (HBM), makes systems like the Xilinx U280 credible platforms for linear solvers which oft…
RedThreads: An Interface for Application-level Fault Detection/Correction through Adaptive Redundant Multithreading
Saurabh Hukerikar, Keita Teranishi, Pedro C. Diniz +1
In the presence of accelerated fault rates, which are projected to be the norm on future exascale systems, it will become increasingly difficult for high-performance computing (HPC…
Rolex: Resilience-Oriented Language Extensions for Extreme-Scale Systems
Saurabh Hukerikar, Robert F. Lucas
Future exascale high-performance computing (HPC) systems will be constructed from VLSI devices that will be less reliable than those used today, and faults will become the norm, no…