P4言語を用いたパケット分類アルゴリズムに関する研究

パケット・クラシファイアとは、コンピュータネットワークにおいてネットワーク機器に到着したパケットをグループに分類するメカリズムである。特定の処理のためにパケットを区別して分離する必要があるサービス、例えば、ファイアウォールやサービス品質などのカスタマイズネットワークサービスなどを提供するためにルータでのパケットを分類するのは極めて重要である。パケット分類に関するアルゴリズムがいくつかの研究で提案されている。分類の性能を向上するため、決定木、ヒューリスティックなどを利用した提案がある。しかし、その性能評価は主にハードウェア実装に基づいていたので、アルゴリズムの設計方法、データ構造などソフトウェルーターに適用できない恐れがある。近年、ネットワークプロトコル、ターゲット非依存という特徴をあるP4言語が開発された。P4言語は幅広いのデータプレーンをプログラミングできるように、ネットワークの基本機能に関する表現力豊かな文法設計されています。仮想ネットワーク機能（VNF）に対する研究が流行っている背景のなか、P4言語用いてソフトウェアにおけるパケット分類の実装を研究する必要がある。本研究では、今までネットワークのパケット分類に関するアルゴリズムがP4言語文法による実装を検討する。P4抽象転送モデル中で利用可能なプログラミングフローを議論し、パケット分類の改善に適しているデータ構造を示した。また、異なるアルゴリズムとデータ構造を用いて、P4ソースコードからコンパイルされたソフトウェアルーターの性能評価を行った。電気通信大学201

High-performance Data Management for Whole Slide Image Analysis in Digital Pathology

When dealing with giga-pixel digital pathology in whole-slide imaging, a notable proportion of data records holds relevance during each analysis operation. For instance, when deploying an image analysis algorithm on whole-slide images (WSI), the computational bottleneck often lies in the input-output (I/O) system. This is particularly notable as patch-level processing introduces a considerable I/O load onto the computer system. However, this data management process could be further paralleled, given the typical independence of patch-level image processes across different patches. This paper details our endeavors in tackling this data access challenge by implementing the Adaptable IO System version 2 (ADIOS2). Our focus has been constructing and releasing a digital pathology-centric pipeline using ADIOS2, which facilitates streamlined data management across WSIs. Additionally, we've developed strategies aimed at curtailing data retrieval times. The performance evaluation encompasses two key scenarios: (1) a pure CPU-based image analysis scenario ("CPU scenario"), and (2) a GPU-based deep learning framework scenario ("GPU scenario"). Our findings reveal noteworthy outcomes. Under the CPU scenario, ADIOS2 showcases an impressive two-fold speed-up compared to the brute-force approach. In the GPU scenario, its performance stands on par with the cutting-edge GPU I/O acceleration framework, NVIDIA Magnum IO GPU Direct Storage (GDS). From what we know, this appears to be among the initial instances, if any, of utilizing ADIOS2 within the field of digital pathology. The source code has been made publicly available at https://github.com/hrlblab/adios

Genome-Wide Survey and Expression Analysis of B-Box Family Genes in Cucumber Reveal Their Potential Roles in Response to Diverse Abiotic and Biotic Stresses

As a class of zinc finger transcription factors, B-box (BBX) proteins play diverse roles in numerous biological processes, and they have been identified in a series of plant species in recent years. However, the roles of BBX genes in regulating cucumber growth regulation and stress response have not yet been established. Here, a total of 22 BBX family genes were identified via an analysis of the latest cucumber genome data, which were classified into five groups (I–V) on the basis of their phylogenetic features and number of B-box domains and CCT domains. The CsBBX genes were unevenly distributed across the seven cucumber chromosomes, and segmental duplication was found to play a significant role in the expansion of the cucumber BBX gene family. Gene structure and motif composition analysis suggested that the evolutionarily close CsBBXs have similar conserved motif composition and gene structure. Most CsBBX genes possessed 1–3 introns, and intron gain rather than intron loss could contribute to the different structures of CsBBX genes across different groups during their evolution. Promoter analysis revealed the presence of 13 kinds of hormone-related and nine kinds of stress-related cis-regulatory elements in the promoter regions of these CsBBX genes. Expression analysis via RNA-seq and qRT-PCR suggested that the CsBBX genes exhibit differential expression in different tissues and in response to various abiotic and biotic stresses. This work constitutes a starting point for further revealing the function of the CsBBX genes and sheds light on the potential molecular mechanism of stress resistance in cucumber

Genome-Wide Survey and Expression Analysis of B-Box Family Genes in Cucumber Reveal Their Potential Roles in Response to Diverse Abiotic and Biotic Stresses

As a class of zinc finger transcription factors, B-box (BBX) proteins play diverse roles in numerous biological processes, and they have been identified in a series of plant species in recent years. However, the roles of BBX genes in regulating cucumber growth regulation and stress response have not yet been established. Here, a total of 22 BBX family genes were identified via an analysis of the latest cucumber genome data, which were classified into five groups (I–V) on the basis of their phylogenetic features and number of B-box domains and CCT domains. The CsBBX genes were unevenly distributed across the seven cucumber chromosomes, and segmental duplication was found to play a significant role in the expansion of the cucumber BBX gene family. Gene structure and motif composition analysis suggested that the evolutionarily close CsBBXs have similar conserved motif composition and gene structure. Most CsBBX genes possessed 1–3 introns, and intron gain rather than intron loss could contribute to the different structures of CsBBX genes across different groups during their evolution. Promoter analysis revealed the presence of 13 kinds of hormone-related and nine kinds of stress-related cis-regulatory elements in the promoter regions of these CsBBX genes. Expression analysis via RNA-seq and qRT-PCR suggested that the CsBBX genes exhibit differential expression in different tissues and in response to various abiotic and biotic stresses. This work constitutes a starting point for further revealing the function of the CsBBX genes and sheds light on the potential molecular mechanism of stress resistance in cucumber