Jian-Jia Chen
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View article: Decoding tumor heterogeneity with imaging biomarkers predicts response to TACE plus Immunotherapy and targeted therapy in HCC
Decoding tumor heterogeneity with imaging biomarkers predicts response to TACE plus Immunotherapy and targeted therapy in HCC Open
Background & Aims: This study aims to quantify intratumor heterogeneity (ITH) and identify prognostic imaging biomarkers in patients with hepatocellular carcinoma (HCC) treated with transarterial chemoembolization combined with immune chec…
View article: WCET-Aware Partitioning and Allocation of Disaggregated Networks for Multicore Systems
WCET-Aware Partitioning and Allocation of Disaggregated Networks for Multicore Systems Open
View article: Transfer Schedulability in Periodic Real-Time Systems
Transfer Schedulability in Periodic Real-Time Systems Open
We introduce and study transfer schedulability , a novel concept that describes how properties of a reference schedule derived from a scheduling algorithm \(\mathcal {A}\) are transferred onto another scheduling algorithm \(\mathcal {B}\) …
View article: Quasi-Static Scheduling for Deterministic Timed Concurrent Models on Multi-Core Hardware
Quasi-Static Scheduling for Deterministic Timed Concurrent Models on Multi-Core Hardware Open
To design performant, expressive, and reliable cyber-physical systems (CPSs), researchers extensively perform quasi-static scheduling for concurrent models of computation (MoCs) on multi-core hardware. However, these quasi-static schedulin…
View article: LazyTick: Lazy and Efficient Management of Job Release in Real-Time Operating Systems
LazyTick: Lazy and Efficient Management of Job Release in Real-Time Operating Systems Open
Releasing jobs and performing scheduling decisions in real-time operating systems (RTOSes) is often realized within tick interrupts. In each tick interrupt, a set of tasks that are waiting to release new jobs, namely, the waiting set, is i…
View article: Optimizing Age-of-Information in Piggyback Networks with Recurrent Data Generation
Optimizing Age-of-Information in Piggyback Networks with Recurrent Data Generation Open
Age-of-information (AoI) is a critical metric that quantifies the freshness of data in communication systems. In the era of the Internet of Things (IoT), data collected by resource-constrained devices often need to be transmitted to a cent…
View article: CHRONOS: Compensating Hardware Related Overheads with Native Multi Timer Support for Real-Time Operating Systems
CHRONOS: Compensating Hardware Related Overheads with Native Multi Timer Support for Real-Time Operating Systems Open
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 all tasks in the systems. In order to establish a connection…
View article: Modeling and Simulating Emerging Memory Technologies: A Tutorial
Modeling and Simulating Emerging Memory Technologies: A Tutorial Open
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, simulators play a crucial role in architectural exploration…
View article: Realizing Hardware-Optimized General Tree-Based Data Structures for Heterogeneous System Classes
Realizing Hardware-Optimized General Tree-Based Data Structures for Heterogeneous System Classes Open
Tree-based data structures are ubiquitous across applications. Therefore, a multitude of different tree implementations exist. However, while these implementations are diverse, they share a tree structure as the underlying data structure. …
View article: WCDT: Systematic WCET Optimization for Decision Tree Implementations
WCDT: Systematic WCET Optimization for Decision Tree Implementations Open
Machine-learning models are increasingly deployed on resource-constrained embedded systems with strict timing constraints. In such scenarios, the worst-case execution time (WCET) of the models is required to ensure safe operation. Specific…
View article: On the complexity of minimizing energy consumption of partitioning DAG tasks
On the complexity of minimizing energy consumption of partitioning DAG tasks Open
View article: End-To-End Latency of Cause-Effect Chains: A Tutorial
End-To-End Latency of Cause-Effect Chains: A Tutorial Open
In many applications of cyber-physical systems, a sequence of tasks is necessary to perform a certain functionality. For example, from a sensor to an actuator, the first task reads the sensor value (cause), the second task processes the da…
View article: Co-Designing NVM-based Systems for Machine Learning and In-memory Search Applications
Co-Designing NVM-based Systems for Machine Learning and In-memory Search Applications Open
View article: Eliminating Timing Anomalies in Scheduling Periodic Segmented Self-Suspending Tasks with Release Jitter
Eliminating Timing Anomalies in Scheduling Periodic Segmented Self-Suspending Tasks with Release Jitter Open
Ensuring timing guarantees for every individual tasks is critical in real-time systems. Even for periodic tasks, providing timing guarantees for tasks with segmented self-suspending behavior is challenging due to timing anomalies, i.e., th…
View article: On the Limitations of Language Targeted Pruning: Investigating the Calibration Language Impact in Multilingual LLM Pruning
On the Limitations of Language Targeted Pruning: Investigating the Calibration Language Impact in Multilingual LLM Pruning Open
Recent advances in large language model (LLM) pruning have shown state-of-the-art (SotA) compression results in post-training and retraining-free settings while maintaining high predictive performance. However, previous research mainly con…
View article: Bridging the Gap between ROS~2 and Classical Real-Time Scheduling for Periodic Tasks
Bridging the Gap between ROS~2 and Classical Real-Time Scheduling for Periodic Tasks Open
The Robot Operating System 2 (ROS~2) is a widely used middleware that provides software libraries and tools for developing robotic systems. In these systems, tasks are scheduled by ROS~2 executors. Since the scheduling behavior of the defa…
View article: Language-Based Deployment Optimization for Random Forests (Invited Paper)
Language-Based Deployment Optimization for Random Forests (Invited Paper) Open
Arising popularity for resource-efficient machine learning models makes random forests and decision trees famous models in recent years. Naturally, these models are tuned, optimized, and transformed to feature maximally low-resource consum…
View article: TREE: Tree Regularization for Efficient Execution
TREE: Tree Regularization for Efficient Execution Open
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 optimization of the chosen model with regard to execution time…
View article: Immune checkpoint inhibitors and anti-vascular endothelial growth factor antibody/tyrosine kinase inhibitors with or without transarterial chemoembolization as first-line treatment for advanced hepatocellular carcinoma (CHANCE2201): a target trial emulation study
Immune checkpoint inhibitors and anti-vascular endothelial growth factor antibody/tyrosine kinase inhibitors with or without transarterial chemoembolization as first-line treatment for advanced hepatocellular carcinoma (CHANCE2201): a target trial emulation study Open
View article: Register Your Forests: Decision Tree Ensemble Optimization by Explicit CPU Register Allocation
Register Your Forests: Decision Tree Ensemble Optimization by Explicit CPU Register Allocation Open
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. Along such tool chains, abstractions have to be applied. This…
View article: On the Complexity of Minimizing Energy Consumption of Partitioning DAG Tasks
On the Complexity of Minimizing Energy Consumption of Partitioning DAG Tasks Open
We study a graph partition problem where we are given a directed acyclic graph (DAG) whose vertices and arcs can be respectively regarded as tasks and dependencies among tasks. The objective of the problem is to minimize the total energy c…
View article: Issue Information
Issue Information Open
No abstract is available for this article.
View article: Dawn of the Dead(line Misses): Impact of Job Dismiss on the Deadline Miss Rate
Dawn of the Dead(line Misses): Impact of Job Dismiss on the Deadline Miss Rate Open
Occasional deadline misses are acceptable for soft real-time systems. Quantifying probabilistic and deterministic characteristics of deadline misses is therefore essential to ensure that deadline misses indeed happen only occasionally. Thi…
View article: Nsbbs are Associated with Improved Survival in Intermediate-Stage Hcc with Clinically Evident Portal Hypertension Following Tace
Nsbbs are Associated with Improved Survival in Intermediate-Stage Hcc with Clinically Evident Portal Hypertension Following Tace Open
View article: Eliminating Timing Anomalies in Scheduling Periodic Segmented Self-Suspending Tasks with Release Jitter
Eliminating Timing Anomalies in Scheduling Periodic Segmented Self-Suspending Tasks with Release Jitter Open
View article: Message from the Program, Track, and General Chairs
Message from the Program, Track, and General Chairs Open
On behalf of the IEEE Technical Committee on Real-Time Systems (TCRTS), it is our pleasure to welcome you to the 44th IEEE Real-Time Systems Symposium (RTSS 2023) during December 5 - 8, 2023 in Taipei. Over the past 44 years, RTSS has esta…
View article: Special Session - Non-Volatile Memories: Challenges and Opportunities for Embedded System Architectures with Focus on Machine Learning Applications
Special Session - Non-Volatile Memories: Challenges and Opportunities for Embedded System Architectures with Focus on Machine Learning Applications Open
This paper explores the challenges and opportunities of integrating non-volatile memories (NVMs) into embedded systems for machine learning. NVMs offer advantages such as increased memory density, lower power consumption, non-volatility, a…
View article: Unlocking Efficiency in BNNs: Global by Local Thresholding for Analog-Based HW Accelerators
Unlocking Efficiency in BNNs: Global by Local Thresholding for Analog-Based HW Accelerators Open
For accelerating Binarized Neural Networks (BNNs), analog computing-based crossbar accelerators, utilizing XNOR gates and additional interface circuits, have been proposed. Such accelerators demand a large amount of analog-to-digital conve…
View article: Probabilistic Reaction Time Analysis
Probabilistic Reaction Time Analysis Open
In many embedded systems, for instance, in the automotive, avionic, or robotics domain, critical functionalities are implemented via chains of communicating recurrent tasks. To ensure safety and correctness of such systems, guarantees on t…
View article: HW/SW Codesign for Robust and Efficient Binarized SNNs by Capacitor Minimization
HW/SW Codesign for Robust and Efficient Binarized SNNs by Capacitor Minimization Open
Using accelerators based on analog computing is an efficient way to process the immensely large workloads in Neural Networks (NNs). One example of an analog computing scheme for NNs is Integrate-and-Fire (IF) Spiking Neural Networks (SNNs)…