1 citations · 1 across the 3 of their papers we have counts for
3 papers
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…
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…
Scaling up HBM Efficiency of Top-K SpMV for Approximate Embedding Similarity on FPGAs
Alberto Parravicini, Luca Giuseppe Cellamare, Marco Siracusa +1
Top-K SpMV is a key component of similarity-search on sparse embeddings. This sparse workload does not perform well on general-purpose NUMA systems that employ traditional caching…