Application Launch Time Research Articles

Method for Profile-Guided Optimization of Android Applications Using Random Forest

When choosing a smartphone, many users are guided by the performance of smartphones and the speed of applications. Because it is difficult to measure the application speed directly, the speed of the application startup is considered and used for comparison. Android runtime (ART) uses several technologies to speed up applications. The first approach is the just-in-time (JIT) compilation of frequently used methods at runtime. The second approach is to compile entire application code ahead of time (AOT). The performance profile is a way to strike a balance between JIT and AOT. The runtime optimization features were introduced in Android Nougat in form of profile-guided optimization (PGO). By aggregating data from a multiplicity of users and devices in Play Store, ART profiling significantly speeds up this process and makes its outcome available to all users alike. We propose a machine learning based method called SPMLGen for generating application profiles used in the optimization. We avoid time delays caused by the need to collect information in advance to perform optimization and ensure user privacy. With profiles generated by SPMLGen, we obtain approximately the same application launch time as with profiles from Play Store. Measurements were taken on Samsung Galaxy S22 and A52 devices with Android 12 firmware and several dozen Samsung applications.

Context-Aware File I/O Management System for Mobile Devices

Mobile devices such as smartphones and tablets have become widespread, and studies are being conducted to improve the convenience of smartphone users. The I/O performance is considered an important factor affecting the quality of the smartphone user experience. Therefore, methods for retaining applications with a high launch frequency in the main memory, improving the I/O stack of the smartphone operating system, and a new file system for improving the I/O performance have been actively studied. However, there is no information sharing system between the I/O stacks in a smartphone operating system. Existing studies suffer from limitations in improving the file I/O performance because the upper- and lower-layer information of the I/O stack was not considered simultaneously. In this paper, we propose a context-aware file I/O management system (CAFIO) for analyzing context information collected from various layers of the I/O stack and sharing them between the layers. CAFIO collects smartphone application usage patterns and combines them with the lower-layer I/O information to improve the launch speed and I/O latency of an application. CAFIO exhibits average improvements of 26% in application launch time and 45% in cache hit ratio, as well as a read speed 63% faster than that of existing file I/O management systems.

Factors Affecting Application Launch Time with Android OS

Android OS is developing very fast, and because of being an open source OS, it is vulnerable to many problems that are manifested to users directly or indirectly. Poor application launch time is one of these problems. In this paper, a set of sixteen experiments is established to distinguish the factors that have the most evident effects on application launch time in Android mobiles. These factors are application, launch and kill, events, and storage. Mann Kendall (MK) test, one way analysis of variance (ANOVA), and Design of Experiment (DOE) are used to prove the influence of factors statistically. As a result of the experiments, the application factor, especially the third party applications level, has the most prominent effects on application launch time, followed by launch and Kill and events, while storage had the least influence.

$ezswap$ : Enhanced Compressed Swap Scheme for Mobile Devices

The limited memory capacity of mobile devices leads to the popular use of compressed swap schemes, which reduce the I/O operations involving the swapping in and out of infrequently accessed pages. However, most of the current compressed swap schemes indiscriminately compress and store all swap-out pages. Considering that both energy and computing power are scarce resources in mobile devices, and modern applications frequently deal with already-compressed multimedia data, this blind approach may cause adverse impacts. In addition, they focus only on anonymous pages and not on file-mapped pages, because the latter are backed by on-disk files. However, our observations revealed that, in mobile devices, file-mapped pages consume significantly more memory than anonymous pages. Last but not least, most of the current compressed swap schemes blindly follow the least-recently-used (LRU) discipline when choosing the victim pages for replacement, not considering the compression ratio or data density of the cached pages. To overcome the aforementioned problems and maximize the memory efficiency, we propose a compressed swap scheme, called enhanced zswap (ezswap), for mobile devices. ezswap accommodates not only anonymous pages, but also clean file-mapped pages. It estimates the compression ratio of incoming pages with their information entropy, and selectively compresses and caches the pages only with beneficial compression ratios. In addition, its admission control and cache replacement algorithms are based on a cost-benefit model that considers not only the access recency of cached pages but also their information density and expected eviction cost. The proposed scheme was implemented in the Linux kernel for Android. Our evaluation with a series of commercial applications demonstrated that it reduced the amount of flash memory read by up to 55%, thereby improving the application launch time by up to 22% in comparison to the original zswap.

ClusterFetch: A Lightweight Prefetcher for Intensive Disk Reads

By overlapping disk accesses with computation-intensive operations, prefetching can reduce delays in launching an application and in loading significant amounts of data while the application is running. The key to effective prefetching is making the tradeoff between the mining accuracy of selecting relevant blocks, and the time to decide those blocks. To address this problem, we propose a new prefetcher called ClusterFetch . In its learning mode, ClusterFetch detects periods of intensive disk accesses by monitoring the speed at which read requests are queued; it re-organizes these reads and locates the file opened by the application just before each such period. During subsequent runs of the same application, ClusterFetch prefetches the data associated with the opening of a “trigger” file. Our experimental results show that ClusterFetch implemented in Linux can reduce the application launch time by up to 41.3 percent and the loading time by up to 38.2 percent, while taking up less than 200 KB of main memory.

Exploiting I/O Reordering and I/O Interleaving to Improve Application Launch Performance

Application prefetchers improve application launch performance through either I/O reordering or I/O interleaving. However, there has been no proposal to combine the two techniques together, missing the opportunity for further optimization. We present a new application prefetching technique to take advantage of both the approaches. We evaluated our method with a set of applications to demonstrate that it reduces cold start application launch time by 50%, which is an improvement of 22% from the I/O reordering technique.

Revisiting swapping in mobile systems with SwapBench

Mobile systems such as smartphones and tablets are re-adopting swapping–a mature but rarely used OS feature–to extend memory capacity without adding more DRAM, especially low-end devices. This resurgence of swapping in mobile systems has inspired both traditional “off-the-rack” schemes and new approaches based on compression and new hardware. Their vastly different designs, however, make them difficult for system designers to measure, compare and revise. In this paper, we first propose an evaluation framework, SwapBench, to appraise swap schemes and focus on two important but overlooked metrics: application launch and switch. And cross-validation with microbenchmarks shows that SwapBench is accurate. Then, we present the first comprehensive evaluation from three dimensions: system architecture, application launch time and application switch delays, to understand and summarize the impacts of swapping in mobile systems. Finally, based on the findings from SwapBench, we give our conclusion and suggestions of different approaches to swapping in mobile systems.

응용프로그램의 기동시간 단축을 위한 파일 시스템 수준의 SSD 캐싱 기법

Application launch time is an important performance metric to user experience in desktop and laptop environment, which mostly depends on the performance of secondary storage. Application launch times can be reduced by utilizing solid-state drive (SSD) instead of hard disk drive (HDD). However, considering a cost-performance trade-off, utilizing SSDs as caches for slow HDDs is a practicable alternative in reducing the application launch times. We propose a new SSD caching scheme which migrates data blocks from HDDs to SSDs. Our scheme operates entirely in the file system level and does not require an extra layer for mapping SSD-cached data that is essential in most other schemes. In particular, our scheme does not incur mapping overheads that cause significant burdens on the main memory, CPU, and SSD space for mapping table. Experimental results conducted with 8 popular applications demonstrate our scheme yields 56% of performance gain in application launch, when data blocks along with metadata are migrated.

Accelerating Application Start-up with Nonvolatile Memory in Android Systems

Application launch time in mobile systems is critical in many cases because it can adversely affect user experience. Android has employed several software techniques to reduce application launch time. For example, Android shares memory space among applications to reduce the loading time of libraries. It also keeps applications in memory, even after the applications are terminated, to reduce start-up time. However, not much research has been done from a hardware perspective to reduce application launch time. In this article, the authors analyze memory usage patterns of Android applications and suggest several hardware optimization techniques. They also demonstrate the benefit of using a phase-change memory such as nonvolatile memory to accelerate start-up time.

브레이크포인트를 이용한 범용 워크로드 프리페칭 프레임워크

Application loading speed can be improved by timely prefetching disk blocks likely to be needed by an application. However, existing prefetchers -- if they are not specialized to a particular application -- incur high overheads and are poor at identifying the blocks that will actually be required. There are many sequences in which blocks may be needed and, even if two access sequences are identical, block tracing and access timings can be affected significantly by the state of the buffer cache. We propose a new application-independent software-based prefetching technique, in which breakpoints are inserted at appropriate places in an application to collect the information on correlations between the blocks and to prefetch the potential blocks ahead of their schedule based on it. Experiments on an HDD-based desktop PC demonstrated an average 30% reduction in application launch time and 15% in general I/O, while reducing the wasted overhead.

Selective memory deduplication for cost efficiency in mobile smart devices

Memory deduplication, which can remedy memory scarcity in mobile systems, can hardly be used due to its high computation cost. This paper proposes a computation efficient memory deduplication scheme that avoids unnecessary computations for memory deduplication. To make it efficient, the proposed scheme gets rid of pages, which are unlikely to be deduplicated, from the target of memory deduplication. This exclusion is performed in time-domain and in space-domain by exploiting the characteristics of mobile applications. The prototype implementation shows significant computation cost reduction while providing the same memory savings as in previous approaches. The saved memory is used for improving application launch time as well.

ACM HotMobile 2013 Poster

This paper presents a novel prefetching technique to reduce application launch time for mobile devices. The proposed method traces disk access accurately during an application launch and prefetches them in efficient way at its subsequent launches. The key idea is to parallelize the use of processor and flash disk while exploiting multi-core and internal parallelism on flash disk. The proposed prefetcher implemented on a mobile Meego platform has achieved a 28.1% reduction of application launch time with 6 popular applications.

A compressed file system manager for flash memory based consumer electronics devices

NAND flash memory is widely used as secondary storage in portable consumer electronics devices such as smartphones and digital cameras. These devices often employ a compressed file system to efficiently manage the limited storage space. However, retrieving data from a compressed file system incurs substantial delays in launching applications due to additional decompression procedures at run time. This paper presents an efficient compressed file system manager (CFSM) that reduces the application launch time in portable consumer electronics devices. CFSM uses two novel techniques. One is the selective decompression that reduces the user-perceived latency by decompressing only the actually requested data acquired by a bulk read. The other technique is cost-aware replacement that preferentially evicts data from uncompressed file systems when memory is full because they are quicker to access than compressed data. A prototype of CFSM has been implemented on the Linux operating system. Measurement studies show that CFSM reduces the application launch latency by 28% on average compared to the well-known CramFS compressed file system.

안드로이드 응용의 응답 시간 향상을 위한 트레이스 기반 프리컴파일 기법

Recently, to improve the user response times of Android applications, several studies have been proposed to combine the idea of Ahead-of-Time compilation into Dalvik virtual machine, which uses Just-in-Time compilation. The studies, however, require modifications of the Dalvik executables of target applications, thus are difficult to be adopted for legacy applications already deployed. This paper proposes a JITwP(JIT with Precompile) technique that precompiles hot traces at application launch time with no modification of the Dalvik executable. It improves the user response times of target applications by providing precompile hints prepared offline. Our experimental results demonstrate a 4% improvement in terms of execution time for the Web browser application.

Improving Application Launch Performance on Solid State Drives

Application launch performance is of great importance to system platform developers and vendors as it greatly affects the degree of users’ satisfaction. The single most effective way to improve application launch performance is to replace a hard disk drive (HDD) with a solid state drive (SSD), which has recently become affordable and popular. A natural question is then whether or not to replace the traditional HDD-aware application launchers with a new SSD-aware optimizer. We address this question by analyzing the inefficiency of the HDD-aware application launchers on SSDs and then proposing a new SSD-aware application prefetching scheme, called the Fast Application STarter (FAST). The key idea of FAST is to overlap the computation (CPU) time with the SSD access (I/O) time during an application launch. FAST is composed of a set of user-level components and system debugging tools provided by Linux OS (operating system). Hence, FAST can be easily deployed in any recent Linux versions without kernel recompilation. We implement FAST on a desktop PC with an SSD running Linux 2.6.32 OS and evaluate it by launching a set of widely-used applications, demonstrating an average of 28% reduction of application launch time as compared to PC without a prefetcher.

Mapping communication layouts to network hardware characteristics on massive-scale blue gene systems

For parallel applications running on high-end computing systems, which processes of an application get launched on which processing cores is typically determined at application launch time without ...

Exploiting SSD parallelism to accelerate application launch on SSDs

Using an optimised application prefetcher to accelerate the application launch on solid-state drives (SSDs) by exploiting the SSD parallelism is proposed. The proposed prefetcher was implemented on the Linux OS and achieved a 37% reduction of prefetcher execution time, which corresponds to an 18% reduction of application launch time.

IEEE-Compliant IDCT on FPGA-Augmented TriMedia

This paper presents a TriMedia processor extended with an IDCT reconfigurable design, and assesses the performance gain such an extension has when performing MPEG-2 decoding. We first propose the skeleton of an extension of the TriMedia architecture, which consists of a Field-Programmable Gate Array (FPGA)-based Reconfigurable Functional Unit (RFU), a Configuration Unit managing the reconfiguration of the RFU, and their associated instructions. Then, we address the computation of the 8 × 8 (2-D) IDCT on such extended TriMedia and propose a scheme to implement the 1-D IDCT operation on the RFU. When mapped on an ACEX EP1K100 FPGA from Altera, the proposed 1-D IDCT exhibits a latency of 16 and a recovery of 2 TriMedia@200 MHz cycles, and occupies 45% of the logic cells of the device. By configuring the 1-D IDCT on the RFU at application launch-time, the IEEE-compliant 2-D IDCT can be computed with the throughput of 1/32 IDCT/cycle. This figure translates to an improvement over the standard TriMedia of more than 40% in terms of computing time when 2-D IDCT is carried out in the framework of MPEG-2 decoding. Finally, the proposed reconfigurable IDCT is compared to a number of existing designs.