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In multi-core architectures, the last-level cache (LLC) is often shared between cores. Sharing the LLC leads to inter-core interference, which impacts system performance and predictability. This means that tasks running in parallel on different ...

Interference between tasks running on separate cores in multi-core processors is a major challenge to predictability for real-time systems, and a source of over-estimation of worst-case execution duration bounds. This paper investigates how the ...

In today’s multiprocessor systems-on-a-chip, the shared memory subsystem is a known source of temporal interference. The problem causes logically independent cores to affect each other’s performance, leading to pessimistic worst-case execution ...

To effectively deploy the scaling-up Deep Neural Networks (DNN), the architecture of deep learning accelerators has evolved to multi-core architecture. Deploying these models to multi-core neural processor units (NPU) requires intricate processes such ...

While speeding up cryptography tasks can be accomplished by using a multi-core architecture to parallelize computation, one of the major challenges is optimizing power consumption. In principle, depending on the computation workload, individual ...

With the widespread adoption of deep neural networks (DNNs) across applications, there is a growing demand for DNN deployment solutions that can seamlessly support multi-tenant execution. This involves simultaneously running multiple DNN workloads on ...

This paper is based on the Zynq UltraScale plus EV series MPSoc hardware platform. To meet the demand of 1080P@500FPS high-speed video with large capacity data storage and high performance, multiple Cortex-A53 cores on the ARM side of the processor are ...

In the field of data mining, high utility itemset mining (HUIM) is a relevant mining task, with the aim of analyzing customer transaction databases. HUIM consists of exploiting the set of items that are often purchased together and ...

• Parallelism is applied at many parts of the algorithm to improve mining performance.

This paper presents a parallel implementation of a fixed-point algorithm for wrapped phase denoising. The model based on total variation efficiently estimates discontinuous phase maps and further incorporates the Pythagorean trigonometric identity ...$\mathrm{}$$\mathrm{}$

Deep neural networks (DNNs) are widely used in modern AI systems, and their dedicated accelerators have become a promising option for edge scenarios due to the energy efficiency and high performance. Since the DNN model requires ...

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• A mixed precision structure to process different effective bit-width weights separately.

Timing verification of multi-core systems is complicated by contention for shared hardware resources between co-running tasks on different cores. This paper introduces the Multi-core Resource Stress and Sensitivity (MRSS) task model that ...

Defect prediction in software development is a very active topic of study. Software defect prediction (SDP) findings give the list of defect-prone source code artefacts, enabling quality assurance teams to efficiently allocate limited resources ...

Set similarity join (SSJ) is a well studied problem with many algorithms proposed to speed up its performance. However, its scalability and performance are rarely discussed in modern multicore environments. Existing algorithms assume a ...

• Multi-threading has not yet been considered to speed up set similarity joins.
• ...

Dataflow is a parallel and generic model of computation that is agnostic of the underlying multi/many-core architecture executing it. State-of-the-art frameworks allow fast development of dataflow applications providing memory, communicating, and ...$\mathrm{}$

Dynamic voltage and frequency scaling (DVFS) is a widely used solution to reduce power consumption. Modern multi-core architectures support core-level DVFS, where each core has its own power supply and can change its frequency ...

• The optimal frequency setting of a core-level DVFS system is proved. This frequency setting can minimize the total power consumption when core number is ...

This paper presents a declarative approach for building parallel local search algorithms. The goal is to easily achieve speed improvements thanks to the growth both in multi-core hardware and the massive availability of distributed computing power,...

Fractal image compression is a lossy compression technique based on the iterative function system, which can be used to reduce the storage space and increase the speed of data transmission. The main disadvantage of fractal image compression is the ...$\mathrm{}$$\mathrm{}$

In this paper, we present a parallel implementation of a fixed-point algorithm for finding the solution of the total variation model for phase demodulation. The total variation model is efficient in estimating discontinuous phase maps, background ...

Sobel edge detection is widely used in computer vision and image processing but its processing time becomes a serious problem in real-time environments, especially when an image is very large. Instead of utilizing a hardware-...

This paper proposes a systematic three-stage methodology for migrating complex real-time industrial software systems from single-core to multi-core computing platforms. Single-core platforms have limited computational capabilities that ...