9 citations · 18 across the 5 of their papers we have counts for
7 papers
Proceedings of the DATE Friday Workshop on System-level Design Methods for Deep Learning on Heterogeneous Architectures (SLOHA 2021)
Frank Hannig, Paolo Meloni, Matteo Spallanzani +1
This volume contains the papers accepted at the first DATE Friday Workshop on System-level Design Methods for Deep Learning on Heterogeneous Architectures (SLOHA 2021), held virtua…
Symbolic Loop Compilation for Tightly Coupled Processor Arrays
Michael Witterauf, Dominik Walter, Frank Hannig +1
Loop compilation for Tightly Coupled Processor Arrays (TCPAs), a class of massively parallel loop accelerators, entails solving NP-hard problems, yet depends on the loop bounds and…
HipaccVX: Wedding of OpenVX and DSL-based Code Generation
M. Akif Özkan, Burak Ok, Bo Qiao +2
Writing programs for heterogeneous platforms optimized for high performance is hard since this requires the code to be tuned at a low level with architecture-specific optimizations…
Utilizing Explainable AI for Quantization and Pruning of Deep Neural Networks
Muhammad Sabih, Frank Hannig, Juergen Teich
For many applications, utilizing DNNs (Deep Neural Networks) requires their implementation on a target architecture in an optimized manner concerning energy consumption, memory req…
AnyHLS: High-Level Synthesis with Partial Evaluation
M. Akif Özkan, Arsène Pérard-Gayot, Richard Membarth +5
FPGAs excel in low power and high throughput computations, but they are challenging to program. Traditionally, developers rely on hardware description languages like Verilog or VHD…
Automatic Optimization of Hardware Accelerators for Image Processing
Oliver Reiche, Konrad Häublein, Marc Reichenbach +3
In the domain of image processing, often real-time constraints are required. In particular, in safety-critical applications, such as X-ray computed tomography in medical imaging or…