2 citations · 3 across the 4 of their papers we have counts for
4 papers
Fast Entropy Decoding for Sparse MVM on GPUs
Emil Schätzle, Tommaso Pegolotti, Markus Püschel
We present a novel, practical approach to speed up sparse matrix-vector multiplication (SpMVM) on GPUs. The novel key idea is to apply lossless entropy coding to further compress t…
QIGen: Generating Efficient Kernels for Quantized Inference on Large Language Models
Tommaso Pegolotti, Elias Frantar, Dan Alistarh +1
We present ongoing work on a new automatic code generation approach for supporting quantized generative inference on LLMs such as LLaMA or OPT on off-the-shelf CPUs. Our approach i…
SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks
Mahdi Nikdan, Tommaso Pegolotti, Eugenia Iofinova +2
We provide a new efficient version of the backpropagation algorithm, specialized to the case where the weights of the neural network being trained are sparse. Our algorithm is gene…
Fast Möbius and Zeta Transforms
Tommaso Pegolotti, Bastian Seifert, Markus Püschel
Möbius inversion of functions on partially ordered sets (posets) is a classical tool in combinatorics. For finite posets it consists of two, mutually inverse, linear…