28 citations · 54 across the 5 of their papers we have counts for
4 papers · 1 filter
A System Development Kit for Big Data Applications on FPGA-based Clusters: The EVEREST Approach
Christian Pilato, Subhadeep Banik, Jakub Beranek +28
Modern big data workflows are characterized by computationally intensive kernels. The simulated results are often combined with knowledge extracted from AI models to ultimately sup…
A Survey on Design Methodologies for Accelerating Deep Learning on Heterogeneous Architectures
Serena Curzel, Fabrizio Ferrandi, Leandro Fiorin +15
Given their increasing size and complexity, the need for efficient execution of deep neural networks has become increasingly pressing in the design of heterogeneous High-Performanc…
A Survey on Deep Learning Hardware Accelerators for Heterogeneous HPC Platforms
Cristina Silvano, Daniele Ielmini, Fabrizio Ferrandi +19
Recent trends in deep learning (DL) have made hardware accelerators essential for various high-performance computing (HPC) applications, including image classification, computer vi…
De-specializing an HLS library for Deep Neural Networks: improvements upon hls4ml
Serena Curzel, Nicolò Ghielmetti, Michele Fiorito +1
Custom hardware accelerators for Deep Neural Networks are increasingly popular: in fact, the flexibility and performance offered by FPGAs are well-suited to the computational effor…