102 citations · 196 across the 10 of their papers we have counts for
4 papers · 1 filter
CODAG: Characterizing and Optimizing Decompression Algorithms for GPUs
Jeongmin Park, Zaid Qureshi, Vikram Mailthody +10
Data compression and decompression have become vital components of big-data applications to manage the exponential growth in the amount of data collected and stored. Furthermore, b…
Understanding the Effect of the Long Tail on Neural Network Compression
Harvey Dam, Vinu Joseph, Aditya Bhaskara +3
Network compression is now a mature sub-field of neural network research: over the last decade, significant progress has been made towards reducing the size of models and speeding…
ArctyrEX : Accelerated Encrypted Execution of General-Purpose Applications
Charles Gouert, Vinu Joseph, Steven Dalton +3
Fully Homomorphic Encryption (FHE) is a cryptographic method that guarantees the privacy and security of user data during computation. FHE algorithms can perform unlimited arithmet…
Stream-K: Work-centric Parallel Decomposition for Dense Matrix-Matrix Multiplication on the GPU
Muhammad Osama, Duane Merrill, Cris Cecka +2
We introduce Stream-K, a work-centric parallelization of matrix multiplication (GEMM) and related computations in dense linear algebra. Whereas contemporary decompositions are prim…