38 citations · 106 across the 12 of their papers we have counts for
14 papers
Hardware/Software Co-Design of RISC-V Extensions for Accelerating Sparse DNNs on FPGAs
Muhammad Sabih, Abrarul Karim, Jakob Wittmann +2
The customizability of RISC-V makes it an attractive choice for accelerating deep neural networks (DNNs). It can be achieved through instruction set extensions and corresponding cu…
Evaluation of CGRA Toolchains
Dominik Walter, Marita Halm, Daniel Seidel +4
Increasing demands for computing power also propel the need for energy-efficient SoC accelerator architectures. One class for such accelerators are so-called processor arrays, whic…
Mapping and Execution of Nested Loops on Processor Arrays: CGRAs vs. TCPAs
Dominik Walter, Marita Halm, Daniel Seidel +4
Increasing demands for computing power also propel the need for energy-efficient SoC accelerator architectures. One class of such accelerators are so-called processor arrays, which…
microYOLO: Towards Single-Shot Object Detection on Microcontrollers
Mark Deutel, Christopher Mutschler, Jürgen Teich
This work-in-progress paper presents results on the feasibility of single-shot object detection on microcontrollers using YOLO. Single-shot object detectors like YOLO are widely us…
On-Device Training of Fully Quantized Deep Neural Networks on Cortex-M Microcontrollers
Mark Deutel, Frank Hannig, Christopher Mutschler +1
On-device training of DNNs allows models to adapt and fine-tune to newly collected data or changing domains while deployed on microcontroller units (MCUs). However, DNN training is…
To Spike or Not to Spike? A Quantitative Comparison of SNN and CNN FPGA Implementations
Patrick Plagwitz, Frank Hannig, Jürgen Teich +1
Convolutional Neural Networks (CNNs) are widely employed to solve various problems, e.g., image classification. Due to their compute- and data-intensive nature, CNN accelerators ha…
Combining Multi-Objective Bayesian Optimization with Reinforcement Learning for TinyML
Mark Deutel, Georgios Kontes, Christopher Mutschler +1
Deploying deep neural networks (DNNs) on microcontrollers (TinyML) is a common trend to process the increasing amount of sensor data generated at the edge, but in practice, resourc…
Efficient Hardware Acceleration of Sparsely Active Convolutional Spiking Neural Networks
Jan Sommer, M. Akif Özkan, Oliver Keszocze +1
Spiking Neural Networks (SNNs) compute in an event-based matter to achieve a more efficient computation than standard Neural Networks. In SNNs, neuronal outputs (i.e. activations)…
DSP-Packing: Squeezing Low-precision Arithmetic into FPGA DSP Blocks
Jan Sommer, M. Akif Özkan, Oliver Keszocze +1
The number of Digital Signal Processor (DSP) resources available in Field Programmable Gate Arrays (FPGAs) is often quite limited. Therefore, full utilization of available DSP reso…
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…
Energy Minimization in DAG Scheduling on MPSoCs at Run-Time: Theory and Practice
Bertrand Simon, Joachim Falk, Nicole Megow +1
Static (offline) techniques for mapping applications given by task graphs to MPSoC systems often deliver overly pessimistic and thus suboptimal results w.r.t. exploiting time slack…
Adaptive Predictive Power Management for Mobile LTE Devices
Peter Brand, Joachim Falk, Jonathan Ah Sue +3
Reducing the energy consumption of mobile phones is a crucial design goal for cellular modem solutions for LTE and 5G standards. In addition to improving the power efficiency of co…
A Scala Prototype to Generate Multigrid Solver Implementations for Different Problems and Target Multi-Core Platforms
Harald Koestler, Christian Schmitt, Sebastian Kuckuk +3
Many problems in computational science and engineering involve partial differential equations and thus require the numerical solution of large, sparse (non)linear systems of equati…