5 citations · 8 across the 12 of their papers we have counts for
12 papers
Schedulable Job-Level Dependencies for Cause-Effect Chains via Graph Neural Networks
Silviu S. Craciunas, Christian Hakert, Jian-Jia Chen +2
Modern automotive software architectures comprise large sets of mixed-criticality functions executing on shared multi-core platforms with strict real-time and end-to-end timing req…
Jump Like A Squirrel: Optimized Execution Step Order for Anytime Random Forest Inference
Daniel Biebert, Christian Hakert, Kay Heider +3
Due to their efficiency and small size, decision trees and random forests are popular machine learning models used for classification on resource-constrained systems. In such syste…
Modeling and Simulating Emerging Memory Technologies: A Tutorial
Yun-Chih Chen, Tristan Seidl, Nils Hölscher +15
Non-volatile Memory (NVM) technologies present a promising alternative to traditional volatile memories such as SRAM and DRAM. Due to the limited availability of real NVM devices,…
CHRONOS: Compensating Hardware Related Overheads with Native Multi Timer Support for Real-Time Operating Systems
Kay Heider, Christian Hakert, Kuan-Hsun Chen +1
The management of timing constraints in a real-time operating system (RTOS) is usually realized through a global tick counter. This counter acts as the foundational time unit for a…
: A Racetrack Register File with Runtime Software Reconfiguration
Christian Hakert, Shuo-Han Chen, Kay Heider +4
Arising disruptive memory technologies continuously make their way into the memory hierarchy at various levels. Racetrack memory is one promising candidate for future memory due to…
Realizing Hardware-Optimized General Tree-Based Data Structures for Heterogeneous System Classes
Daniel Biebert, Christian Hakert, Jian-Jia Chen
Tree-based data structures are ubiquitous across applications. Therefore, a multitude of different tree implementations exist. However, while these implementations are diverse, the…
WCDT: Systematic WCET Optimization for Decision Tree Implementations
Nils Hölscher, Christian Hakert, Georg von der Brüggen +3
Machine-learning models are increasingly deployed on resource-constrained embedded systems with strict timing constraints. In such scenarios, the worst-case execution time (WCET) o…
TREE: Tree Regularization for Efficient Execution
Lena Schmid, Daniel Biebert, Christian Hakert +4
The rise of machine learning methods on heavily resource constrained devices requires not only the choice of a suitable model architecture for the target platform, but also the opt…
Register Your Forests: Decision Tree Ensemble Optimization by Explicit CPU Register Allocation
Daniel Biebert, Christian Hakert, Kuan-Hsun Chen +1
Bringing high-level machine learning models to efficient and well-suited machine implementations often invokes a bunch of tools, e.g.~code generators, compilers, and optimizers. Al…
FLInt: Exploiting Floating Point Enabled Integer Arithmetic for Efficient Random Forest Inference
Christian Hakert, Kuan-Hsun Chen, Jian-Jia Chen
In many machine learning applications, e.g., tree-based ensembles, floating point numbers are extensively utilized due to their expressiveness. Nowadays performing data analysis on…
SoftWear: Software-Only In-Memory Wear-Leveling for Non-Volatile Main Memory
Christian Hakert, Kuan-Hsun Chen, Paul R. Genssler +5
Several emerging technologies for byte-addressable non-volatile memory (NVM) have been considered to replace DRAM as the main memory in computer systems during the last years. The…
Towards Explainable Bit Error Tolerance of Resistive RAM-Based Binarized Neural Networks
Sebastian Buschjäger, Jian-Jia Chen, Kuan-Hsun Chen +6
Non-volatile memory, such as resistive RAM (RRAM), is an emerging energy-efficient storage, especially for low-power machine learning models on the edge. It is reported, however, t…