Read disturb is a phenomenon in which the cells of all unselected wordlines (WLs) within a block are soft programed while reading a selected WL, which causes errors. To solve the problem of read disturb, read reclaim (RR) operations, which migrate deteriorated block data to a new free block, are executed when the read count of the deteriorated block exceeds a preset threshold. RR requires additional operations, such as error correction, reprogramming, block erasure, and occupying I/O. So as the number of RR operations increases, the performance and reliability of the memory degrade. We observe that read disturb affects pages within a block differently according to page types. With this perspective, we propose Page Type-aware Data Migration technique (PTDM) technique, which migrates pages within blocks according to the vulnerability to read disturb. Shifting RR from the conventional block level to the page level improves the efficiency of the memory by reducing data migration. Also, we propose distributing read-hot data into several blocks during migration to reduce read disturb impact. Our experimental results show that the proposed method can reduce the amount of RR data migration and the overall erasure counts by 39.53% and 21.69%, respectively.

Extreme multi-label classification (XMC) aims at finding multiple relevant labels for a given sample from a huge label set at the industrial scale. The XMC problem inherently poses two challenges: scalability and label sparsity - the number of labels is too large, and labels follow the long-tail distribution. To resolve these problems, we propose a novel Mixup-based augmentation method for long-tail labels, called TailMix. Building upon the partition-based model, TailMix utilizes the context vectors generated from the label attention layer. It first selectively chooses two context vectors using the inverse propensity score of labels and the label proximity graph representing the co-occurrence of labels. Using two context vectors, it augments new samples with the long-tail label to improve the accuracy of long-tail labels. Despite its simplicity, experimental results show that TailMix consistently outperforms other augmentation methods on three benchmark datasets, especially for long-tail labels in terms of two metrics, [email protected] and [email protected]

NAND flash-based storage devices (NFSDs) have been widely employed in various systems, including cloud servers as well as mobile devices. The core component of NFSDs is NAND flash memory (NFM) which has several advantages over the conventional hard disk drives (HDDs). An NFSD typically adopts a bunch of NFMs which are operated in parallel for maximizing the I/O throughput. However, optimizing for performance may not be desirable from the power budget (PB) perspective. In other words, concurrent operations of NFMs often drain inordinate current, which leads to the violation of the PB allocated for a storage device. In this article, we propose a novel power management scheme which maximizes concurrent operations of NFMs under the given power constraint. The proposed method quantizes the given power constraint of an NFSD. A quantum also called token is the basic unit of power management. The proposed power management scheme allocates tokens to NFMs and only the NFMs having enough tokens can perform their operations. We call this method multitoken-based power management (MTPM). The critical issue of MTPM is a deadlock which is resolved with the key allocation scheme. Furthermore, we enhance MTPM to improve performance. The extended method called keyless MTPM (KMTPM) improves the overall performance by relaxing the key acquisition requirement and allowing subatomic operations. In the experimental results, we confirm that the proposed methods always meet the given power constraint. The proposed KMTPM improves throughput by 22.85% compared to state of the art technique. In addition, KMTPM only incurs 3.8% of performance overhead and 0.015% of area overhead.

Dynamic random access memory (DRAM) reliability has become one of the critical issues in embedded systems, as DRAM process technology advances with the increase in bit error probability. Unfortunately, redundant error-correction code (ECC) chips cannot be applied to embedded systems since cores and DRAMs are tightly coupled without a dual in-line memory module (DIMM) slot to account for the form factor, cost, and limited pin count. Therefore, ECC parities are typically placed in the same physical array where the user and system data reside. This coexistence eventually deteriorates data locality, which could be the critical factor in DRAM performance degradation. To address this issue, we propose an ECC scheme called locality-aware compression (LoComp) which integrates a compression algorithm, DRAM data layout, and memory controller especially optimized for embedded systems. We focus on the locality of the dataset and its corresponding metadata, as well as spatial data locality in the design of DRAM data layout, which reduces the number of row activations. The major feature in a compression algorithm is adjusting the misalignment of data streams caused by the data packing in many embedded systems. Moreover, we specialize the memory controller to reduce DRAM access for ECC parities and compression flags. The core technologies for the memory controller are the adoption of a set of small caches for metadata and the support of partial write operation without changing the DRAM interface. LoComp+, an enhanced version of LoComp, further reduces DRAM access for metadata by placing the metadata close to the corresponding data. In the experiment, previous works increase the DRAM access time from 68% to over twice the value compared to ECC DIMM. Whereas, LoComp and LoComp+ show reduced performance degradation by 33% and 48%, respectively. In other words, LoComp and LoComp+ substantially improved performance from between 13% and 33% compared to previous embedded ECC schemes.

As CMOS devices become smaller, the process variations (PVs) and aging variations (AVs) become major issues for circuit reliability and yield. In this paper, we analyze the effects of PVs on aging effects such as hot carrier injection (HCI) and negative bias temperature instability (NBTI). Using Monte Carlo-based transistor-level simulations including principal component analysis, the correlations between PVs and AVs are considered, by which the accuracy of analysis is improved (1.2% for standard deviation and 1.7% for Vth99%) compared to other methods that ignore the correlations, especially in the smaller technology. In addition, we perform regression analysis with various models to improve the efficiency of variation-aware aging analysis. All models show an error rate about 1% for NBTI, and quadratic and custom models show an error rate of about 10% on average for HCI.

As CMOS devices become smaller, process and aging variations become a major issue for circuit reliability and yield. In this paper, we analyze the effects of process variations on aging effects such as hot carrier injection (HCI) and negative bias temperature instability (NBTI). Using Monte-Carlo based transistor-level simulations including principal component analysis (PCA), the correlations between process variations and aging variations are considered. The accuracy of analysis is improved (2-7%) compared to other methods in which the correlations are ignored, especially in smaller technologies.

The multimedia-oriented collaboration is very important for knowledge workers who work together at a distance in pervasive computing environments. In this demonstration, we present a multi-agent-based toolkit to manage the coordination of multiple component services for multimedia-oriented collaboration environments. Based on a multi-agent system, the proposed toolkit is designed to support features such as node configuration for multiple devices, flexible operation of versatile collaboration tools, and session management for multi-party collaboration.

This paper introduces the software design for smart meeting space (SMeet) that enables users to collaborate with remote persons by using a wide range of devices embedded in networked meeting rooms. To enhance the quality of user experience in remote collaboration, SMeet is designed to satisfy several considerations from the integrated view of media, networking, display, and interaction services. We propose a software architecture of SMeet to flexibly associate component services to support high-quality media transport, high-resolution tiled display, and display interaction. We also present an approach to create composite services by combining component services. We explain key issues to dynamically build composite services and to integrate the service composition scheme with the proposed software architecture.

In this paper, we propose a practical media service framework to offer high-quality media service for multiparty collaborative environments. The proposed framework suggests an unified approach to employ various media formats, enable multicast-connectivity and display highresolution videos. It includes media controllers to enable DV (digital video) and HDV (high-definition DV) streaming, announce sessions, and guide the adaptive QoS control. It includes media connectors to enable using UDP tunneling to offer multicast-connectivity. Finally, it supports media producers/consumers to encode, transmit, decode, and render high-quality media. We explore the possibility of proposed framework by implementing a prototype and evaluating it over multicast-enabled network testbed.