In HPC systems, the increasing need for a higher level of concurrency has led to packing more cores within a single chip. However, since multiple processes share memory space, the frequent access to resources in critical sections where only atomic operation has to be executed can result in poor performance. In this paper, we focus on reducing lock contention on the memory management system of an HPC manycore architecture. One of the critical sections causing severe lock contention in the I/O path is in the page management system, which uses multiple Least Recently Used (LRU) lists with a single lock instance. To solve this problem, we propose a Finer-LRU scheme, which optimizes the page reclamation process by splitting LRU lists into multiple sub-lists, each having its own lock instance. Our evaluation result shows that the Finer-LRU scheme can improve sequential write throughput by 57.03% and reduce latency by 98.94% compared to the baseline Linux kernel version 5.2.8 in the Intel Knights Landing (KNL) architecture.

The graphics processing unit (GPU) is extensively used in diverse domains, such as finance, machine learning, and image processing. The GPU can be underutilized as multiple applications may not share the same GPU concurrently owing to a memory oversubscription issue. For example, when applications that require fewer computational resources but a larger GPU memory are running instantaneously, the GPU memory may be insufficient; consequently, the number of GPU applications running simultaneously is restricted, decreasing GPU utilization. Further, it can even stop the execution of applications that are running on the GPU. To this end, we propose FlexGPU, which schedules the kernels of the GPU applications that run on the same GPU according to their features. This framework 1) schedules the kernel at the launching time according to its features to improve GPU utilization and 2) temporarily checkpoints and restores non-dependent content in the GPU memory to/from the host memory, which avoids oversubscription of the GPU when out-of-memory failure occurs and allows more kernels to run concurrently on the GPU. The experimental results show that compared to existing methods, our approach demonstrates a 7 times improvement in performance in terms of execution time and enables a 2.5 times increase in the concurrent execution of applications.

Increasingly, smart phones are becoming one of the most popular mobile devices in personal computing environment. As the need for a variety of mobile applications is increasing, the target mobile platform is a primary concern for mobile application developers. To reduce design complexity for different platforms and enhance the compatibility of applications on various mobile OSes, a JavaScript-based web environment became a main target framework for smart phone applications. Computing-intensive and rich graphics-based applications in a smart phone may fully utilize the CPU, and consume a large amount of the battery power accordingly. In this paper, we propose PIOS, a platform-independent offloading system, which is a delegated system for a mobile web environment. Our evaluation shows that PIOS increases the response time of the application running in the web browser, and enables a high workload application to run on relatively low-end mobile devices. Our web-based offloading architecture creates a new mobile computing environment, and can be applied various OS platforms of mobile clients.

Increasingly, smart phones are becoming one of the most popular mobile devices in personal computing environment. As the need for a variety of mobile applications is increasing, the target mobile platform is a primary concern for mobile application developers. To reduce design complexity for different platforms and enhance the compatibility of applications on various mobile OSes, a JavaScript-based web environment became a main target framework for smart phone applications. Computing-intensive and rich graphics-based applications in a smart phone may fully utilize the CPU, and consume a large amount of the battery power accordingly. In this paper, we propose PIOS, a platform-independent offloading system, which is a delegated system for a mobile web environment. Our evaluation shows that PIOS increases the response time of the application, and reduces power consumption of the device. Our web-based offloading architecture creates a new mobile computing environment.

As the popularity of mobile devices increase, more and more smart phones are being utilized as main computing devices in recent years. Applications for mobile devices have been widely developing even more prevalent than those for PCs. Most mobile applications also integrate with web browsers, with JavaScript serving as an important framework for web-based mobile applications. However, these applications require great amounts of computational power and energy. In addition, relatively low-end mobile devices that pose some limitations in supporting complicated web resource are widely used in developing countries. In this paper, we propose SOME architecture, which is an offloading system for mobile applications, in an effort to reduce the computational cost of mobile devices. We design and implement a delegated system that splits the original JavaScript-based application codes into two parts: a lightweight code for the client and a computationally heavy code to run on a server machine. In our evaluation, our system shows better performance in casual turn-based applications. Overall, the SOME architecture creates a new mobile computing environment that increases the total performance and overcomes resource limitation without platform dependence of mobile clients.