88 citations · 153 across the 10 of their papers we have counts for
4 papers · 1 filter
dCSR: A Memory-Efficient Sparse Matrix Representation for Parallel Neural Network Inference
Elias Trommer, Bernd Waschneck, Akash Kumar
Reducing the memory footprint of neural networks is a crucial prerequisite for deploying them in small and low-cost embedded devices. Network parameters can often be reduced signif…
NMPO: Near-Memory Computing Profiling and Offloading
Stefano Corda, Madhurya Kumaraswamy, Ahsan Javed Awan +3
Real-world applications are now processing big-data sets, often bottlenecked by the data movement between the compute units and the main memory. Near-memory computing (NMC), a mode…
Toward the Design of Fault-Tolerance- and Peak- Power-Aware Multi-Core Mixed-Criticality Systems
Behnaz Ranjbar, Ali Hosseinghorban, Mohammad Salehi +2
Mixed-Criticality (MC) systems have recently been devised to address the requirements of real-time systems in industrial applications, where the system runs tasks with different cr…
Compiler Toolchains for Deep Learning Workloads on Embedded Platforms
Max Sponner, Bernd Waschneck, Akash Kumar
As the usage of deep learning becomes increasingly popular in mobile and embedded solutions, it is necessary to convert the framework-specific network representations into executab…