2 citations · 3 across the 6 of their papers we have counts for
3 papers · 1 filter
SpChar: Characterizing the Sparse Puzzle via Decision Trees
Francesco Sgherzi, Marco Siracusa, Ivan Fernandez +2
Sparse matrix computation is crucial in various modern applications, including large-scale graph analytics, deep learning, and recommender systems. The performance of sparse kernel…
A Mixed Precision, Multi-GPU Design for Large-scale Top-K Sparse Eigenproblems
Francesco Sgherzi, Alberto Parravicini, Marco Domenico Santambrogio
Graph analytics techniques based on spectral methods process extremely large sparse matrices with millions or even billions of non-zero values. Behind these algorithms lies the Top…
Solving Large Top-K Graph Eigenproblems with a Memory and Compute-optimized FPGA Design
Francesco Sgherzi, Alberto Parravicini, Marco Siracusa +1
Large-scale eigenvalue computations on sparse matrices are a key component of graph analytics techniques based on spectral methods. In such applications, an exhaustive computation…