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The importance of physically contiguous memory has increased in modern computing environments, including both low- and high-end systems. Existing physically contiguous memory allocators generally have critical limitations. For example, the most commonly adopted solution, the memory reservation technique, wastes a significant amount of memory space. Scatter/Gather direct memory access (DMA) and input-output memory management units (IOMMUs) avoid this problem by utilizing additional hardware for address space virtualization. However, additional hardware means an increase in costs and power consumption, which is especially disadvantageous for small systems and they do not provide real contiguous memory. Linux Contiguous Memory Allocator (CMA) aims to provide both contiguous memory allocation and to maximize memory utilization based on page migration, but they suffer from unpredictably long latency and a high probability of allocation failure. Therefore, we introduce a new solution to this problem, the guaranteed contiguous memory allocator (GCMA). This guarantees efficient memory space utilization, short latency, and successful allocation. The GCMA uses a reservation scheme and increases memory utilization by sharing the memory with immediately discardable data. Our evaluation of a GCMA on a Raspberry Pi 2 finds a latency that is 15-130 times lower compared to a CMA, and a latency that is up to 10 times lower when taking a photo. Using a large working set in a memory-fragmented high-end system, the GCMA is able to produce a 2.27x speedup.

For the fabrication of high-performance top-gated MoS2 transistors, a uniform atomic layer deposition (ALD) of an ultrathin high-k gate dielectric film without abnormal leakage paths on a MoS2 channel is required. In this study, we fabricated a ~5.2 nm-thick monolithic HfO2 gate dielectric film by utilizing an e-beam-evaporated Hf seed layer (target thickness of 3 nm) prior to the ALD of a HfO2 film (~2 nm). The Hf seed layer was fully converted to HfO2 without metallic residues during the following ALD process, without damages to the Raman and photoluminescence characteristics of the underlying MoS2. The conformal and pinhole-free ALD of the subsequent HfO2 film was verified using conductive atomic force microscopy. In addition, operation of a top-gated MoS2 transistor was demonstrated by integrating the Hf-seeded HfO2 gate dielectric film.

Read-copy update (RCU) can provide ideal scalability for read-mostly workloads, but some believe that it provides only poor performance for updates. This belief is due to the lack of RCU-centric update synchronization mechanisms. RCU instead works with a range of update-side mechanisms, such as locking. In fact, many developers embrace simplicity by using global locking. Logging, hardware transactional memory, or fine-grained locking can provide better scalability, but each of these approaches has limitations, such as imposing overhead on readers or poor scalability on non-uniform memory access (NUMA) systems, mainly due to their lack of NUMA-aware design principles. This paper introduces an RCU extension (RCX) that provides highly scalable RCU updates on NUMA systems while retaining RCU's read-side benefits. RCX is a software-based synchronization mechanism combining hardware transactional memory (HTM) and traditional locking based on our NUMA-aware design principles for RCU. Micro-bench-marks on a NUMA system having 144 hardware threads show RCX has up to 22.6 times better performance and up to 145 times lower HTM abort rates compared to a state-of-the-art RCU/HTM combination. To demonstrate the effectiveness and applicability of RCX, we have applied RCX to parallelize some of the Linux kernel memory management system and an in-memory database system. The optimized kernel and the database show up to 24 and 17 times better performance compared to the original version, respectively.

One common characteristic of modern workloads such as cloud, big data, and machine learning is memory intensiveness. In detail, such workloads tend to have a huge working set and low locality. Especially, the size of working sets is rapidly growing so that cannot be fully accommodated by a DRAM based main memory. Worse yet, the cloud computing systems, which has been pervasive since few decades ago, are continuously reducing the size of DRAM per CPU and encouraging memory overcommitment. Consequently, efficient and effective out-of-core memory management is becoming more important. Though a number of memory management mechanisms for such situations have proposed, manual analysis and optimization are still required for optimal performance of each workload due to the wide variety of data access patterns. However, existing tools for memory access analysis are not appropriate to be used here because those are not designed for extraction of the dynamic data access pattern of modern workloads. When those tools are used for the purpose, those incur unacceptably high overheads for unnecessarily accurate analysis results. To mitigate this situation, we introduce a tool that is designed for the purpose. Basically, the tool employs a memory access tracking technique based on page table entry access bit, which incurs only minimal overhead. It also provides a technique for an effective tradeoff between profiling overheads and accuracy of the output by dynamically adjusting number of tracking regions. By adopting the technique, this tool can control the level of overheads and output accuracy in bounded range that user specified regardless of the size of target workloads. The overhead can be lowered even enough to be used for online target workloads while still providing useful quality of the extracted data access pattern. The main contributions of this paper are: 1) introduce of the data access patterns profiler tool designed for modern memory-intensive workloads, and 2) empirical memory access pattern analysis of various realistic workloads.

Organic light-emitting diodes (OLEDs) have been widely studied because of their various advantages. OLEDs are multi-layered structures consisting of organic and inorganic materials arranged in a heterojunction; the nature of adhesion at their heterogeneous interfaces has a significant effect on their properties. In this study, the origin of macroscopic adhesion was explored in OLEDs using a combination of microscopy techniques applied at different length scales. The different techniques allowed the identification of layers exposed by a peel test, which aided direct characterization of their macroscopic adhesion. Further, the contribution of each exposed layer to macroscopic adhesion could be determined through an analysis of photographic images. Finally, analysis of the local roughness and adhesion confirmed that the interface between an anode and emission layer could play a predominant role in determining the nature of macroscopic adhesion in OLEDs. These results may provide guidelines for exploring the origin of macroscopic adhesion properties through a combination of various microscopy techniques.