Publications

Filtered as: all types - all years - all authors - keyword: Scalable
Sorted by: author
Corresponding bibtex list 

Franchetti, Franz 

  1. Anuva Kulkarni, Jelena Kovacevic and Franz Franchetti
    A Framework for Low Communication Approaches for Large Scale 3D Convolution
    Proc. International Conference on Parallel Processing (ICPP), 2022
  2. N. Kitai, Daisuke Takahashi, Franz Franchetti, T. Katagiri, S. Ohshima and T. Nagai
    An Auto-tuning with Adaptation of A64 Scalable Vector Extension for SPIRAL
    Proc. International Workshop on Automatic Performance Tuning (iWAPT), 2021
  3. Anuva Kulkarni, Jelena Kovacevic and Franz Franchetti
    Massive Scaling of MASSIF: Algorithm Development and Analysis for Simulation on GPUs
    Proc. Platform for Advanced Scientific Computing (PASC), Article 13, pp. 1 - 10, 2020
  4. F. Sadi, Joe Sweeney, Tze-Meng Low, James C. Hoe, Lawrence Pileggi and Franz Franchetti
    Efficient SpMV Operation for Large and Highly Sparse Matrices Using Scalable Multi-way Merge Parallelization
    Proc. MICRO, 2019
  5. F. Sadi, Joe Sweeney, S. McMillan, Tze-Meng Low, James C. Hoe, Lawrence Pileggi and Franz Franchetti
    PageRank Acceleration for Large Graphs with Scalable Hardware and Two-Step SpMV
    Proc. High Performance Extreme Computing (HPEC), 2018

Hoe, James C. 

  1. F. Sadi, Joe Sweeney, Tze-Meng Low, James C. Hoe, Lawrence Pileggi and Franz Franchetti
    Efficient SpMV Operation for Large and Highly Sparse Matrices Using Scalable Multi-way Merge Parallelization
    Proc. MICRO, 2019
  2. F. Sadi, Joe Sweeney, S. McMillan, Tze-Meng Low, James C. Hoe, Lawrence Pileggi and Franz Franchetti
    PageRank Acceleration for Large Graphs with Scalable Hardware and Two-Step SpMV
    Proc. High Performance Extreme Computing (HPEC), 2018

Katagiri, T. 

  1. N. Kitai, Daisuke Takahashi, Franz Franchetti, T. Katagiri, S. Ohshima and T. Nagai
    An Auto-tuning with Adaptation of A64 Scalable Vector Extension for SPIRAL
    Proc. International Workshop on Automatic Performance Tuning (iWAPT), 2021

Kitai, N. 

  1. N. Kitai, Daisuke Takahashi, Franz Franchetti, T. Katagiri, S. Ohshima and T. Nagai
    An Auto-tuning with Adaptation of A64 Scalable Vector Extension for SPIRAL
    Proc. International Workshop on Automatic Performance Tuning (iWAPT), 2021

Kovacevic, Jelena 

  1. Anuva Kulkarni, Jelena Kovacevic and Franz Franchetti
    A Framework for Low Communication Approaches for Large Scale 3D Convolution
    Proc. International Conference on Parallel Processing (ICPP), 2022
  2. Anuva Kulkarni, Jelena Kovacevic and Franz Franchetti
    Massive Scaling of MASSIF: Algorithm Development and Analysis for Simulation on GPUs
    Proc. Platform for Advanced Scientific Computing (PASC), Article 13, pp. 1 - 10, 2020

Kulkarni, Anuva 

  1. Anuva Kulkarni, Jelena Kovacevic and Franz Franchetti
    A Framework for Low Communication Approaches for Large Scale 3D Convolution
    Proc. International Conference on Parallel Processing (ICPP), 2022
  2. Anuva Kulkarni, Jelena Kovacevic and Franz Franchetti
    Massive Scaling of MASSIF: Algorithm Development and Analysis for Simulation on GPUs
    Proc. Platform for Advanced Scientific Computing (PASC), Article 13, pp. 1 - 10, 2020

Low, Tze-Meng 

  1. F. Sadi, Joe Sweeney, Tze-Meng Low, James C. Hoe, Lawrence Pileggi and Franz Franchetti
    Efficient SpMV Operation for Large and Highly Sparse Matrices Using Scalable Multi-way Merge Parallelization
    Proc. MICRO, 2019
  2. F. Sadi, Joe Sweeney, S. McMillan, Tze-Meng Low, James C. Hoe, Lawrence Pileggi and Franz Franchetti
    PageRank Acceleration for Large Graphs with Scalable Hardware and Two-Step SpMV
    Proc. High Performance Extreme Computing (HPEC), 2018

McMillan, S. 

  1. F. Sadi, Joe Sweeney, S. McMillan, Tze-Meng Low, James C. Hoe, Lawrence Pileggi and Franz Franchetti
    PageRank Acceleration for Large Graphs with Scalable Hardware and Two-Step SpMV
    Proc. High Performance Extreme Computing (HPEC), 2018

Nagai, T. 

  1. N. Kitai, Daisuke Takahashi, Franz Franchetti, T. Katagiri, S. Ohshima and T. Nagai
    An Auto-tuning with Adaptation of A64 Scalable Vector Extension for SPIRAL
    Proc. International Workshop on Automatic Performance Tuning (iWAPT), 2021

Ohshima, S. 

  1. N. Kitai, Daisuke Takahashi, Franz Franchetti, T. Katagiri, S. Ohshima and T. Nagai
    An Auto-tuning with Adaptation of A64 Scalable Vector Extension for SPIRAL
    Proc. International Workshop on Automatic Performance Tuning (iWAPT), 2021

Pileggi, Lawrence 

  1. F. Sadi, Joe Sweeney, Tze-Meng Low, James C. Hoe, Lawrence Pileggi and Franz Franchetti
    Efficient SpMV Operation for Large and Highly Sparse Matrices Using Scalable Multi-way Merge Parallelization
    Proc. MICRO, 2019
  2. F. Sadi, Joe Sweeney, S. McMillan, Tze-Meng Low, James C. Hoe, Lawrence Pileggi and Franz Franchetti
    PageRank Acceleration for Large Graphs with Scalable Hardware and Two-Step SpMV
    Proc. High Performance Extreme Computing (HPEC), 2018

Sadi, F. 

  1. F. Sadi, Joe Sweeney, Tze-Meng Low, James C. Hoe, Lawrence Pileggi and Franz Franchetti
    Efficient SpMV Operation for Large and Highly Sparse Matrices Using Scalable Multi-way Merge Parallelization
    Proc. MICRO, 2019
  2. F. Sadi, Joe Sweeney, S. McMillan, Tze-Meng Low, James C. Hoe, Lawrence Pileggi and Franz Franchetti
    PageRank Acceleration for Large Graphs with Scalable Hardware and Two-Step SpMV
    Proc. High Performance Extreme Computing (HPEC), 2018

Sweeney, Joe 

  1. F. Sadi, Joe Sweeney, Tze-Meng Low, James C. Hoe, Lawrence Pileggi and Franz Franchetti
    Efficient SpMV Operation for Large and Highly Sparse Matrices Using Scalable Multi-way Merge Parallelization
    Proc. MICRO, 2019
  2. F. Sadi, Joe Sweeney, S. McMillan, Tze-Meng Low, James C. Hoe, Lawrence Pileggi and Franz Franchetti
    PageRank Acceleration for Large Graphs with Scalable Hardware and Two-Step SpMV
    Proc. High Performance Extreme Computing (HPEC), 2018

Takahashi, Daisuke 

  1. N. Kitai, Daisuke Takahashi, Franz Franchetti, T. Katagiri, S. Ohshima and T. Nagai
    An Auto-tuning with Adaptation of A64 Scalable Vector Extension for SPIRAL
    Proc. International Workshop on Automatic Performance Tuning (iWAPT), 2021
Publication interface designed and implemented by Patra Pantupat, Aliaksei Sandryhaila, and Markus Püschel
Electrical and Computer Engineering, Carnegie Mellon University, 2007