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In these days embedded system have an important role in different Fields and applications like Network embedded system , Real-time embedded systems which supports the mission-critical domains, mostly having the time constraints, Stand-alone…
Microservices architecture has started a new trend for application development for a number of reasons: (1) to reduce complexity by using tiny services; (2) to scale, remove and deploy parts of the system easily; (3) to improve flexibility…
Edge computing requires the complex software interaction of geo-distributed, heterogeneous components. The growing research and industry interest in edge computing software systems has necessitated exploring ways of testing and evaluating…
Solid State Drives (SSDs) are a moving target for system designers: they are black boxes, their internals are undocumented, and their performance characteristics vary across models. There is no appropriate analytical model and experimenting…
Because most optimisations to achieve higher computational performance eventually are limited, parallelism that scales is required. Parallelised hardware alone is not sufficient, but software that matches the architecture is required to…
Machine learning, and eventually true artificial intelligence techniques, are extremely important advancements in astrophysics and astronomy. We explore the application of deep learning using neural networks in order to automate the…
The increasing demands for computing performance have been a reality regardless of the requirements for smaller and more energy efficient devices. Throughout the years, the strategy adopted by industry was to increase the robustness of a…
In deep learning, performance is strongly affected by the choice of architecture and hyperparameters. While there has been extensive work on automatic hyperparameter optimization for simple spaces, complex spaces such as the space of deep…
Quantum computers hold promise to improve the efficiency of quantum simulations of materials and to enable the investigation of systems and properties more complex than tractable at present on classical architectures. Here, we discuss…
Automated game design is a rapidly growing area of research, yet many aspects of game design lie largely unexamined still, as most systems focus on two-dimensional games with clear objectives and goal-oriented gameplay. This paper describes…
Deep neural networks (DNNs) have been shown to outperform conventional machine learning algorithms across a wide range of applications, e.g., image recognition, object detection, robotics, and natural language processing. However, the high…
Many computer systems for calculating the proper organization of memory are among the most critical issues. Using a tier cache memory (along with branching prediction) is an effective means of increasing modern multi-core processors'…
Information exploration tasks are inherently complex, ill-structured, and involve sequences of actions usually spread over many sessions. When exploring a dataset, users tend to experiment higher degrees of uncertainty, mostly raised by…
Nvidia Jetson boards are powerful systems for executing artificial intelligence workloads in edge and mobile environments due to their effective GPU hardware and widely supported software stack. In addition to these benefits, Nvidia Jetson…
The recent decades have seen various attempts at accelerating the process of developing materials targeted towards specific applications. The performance required for a particular application leads to the choice of a particular material…
Computer architecture simulation is essential for evaluating new designs without the need for costly tapeout. The community has developed dozens of valuable simulators that have enabled significant architectural advances. However, using and…
It has been a long time that computer architecture and systems are optimized for efficient execution of machine learning (ML) models. Now, it is time to reconsider the relationship between ML and systems, and let ML transform the way that…
Distributed computing is increasingly being viewed as the next phase of Large Scale Distributed Systems (LSDSs). However, the vision of large scale resource sharing is not yet a reality in many areas - Grid computing is an evolving area of…
Traditional simulations on High-Performance Computing (HPC) systems typically involve modeling very large domains and/or very complex equations. HPC systems allow running large models, but limits in performance increase that have become…
Design space exploration (DSE) plays a crucial role in enabling custom hardware architectures, particularly for emerging applications like AI, where optimized and specialized designs are essential. With the growing complexity of deep neural…