2 citations · 4 across the 6 of their papers we have counts for
3 papers · 1 filter
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…
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…