~ ~ 0 0 TB TB Usable Capacity 可用容量
~460 TB usable from a 3-node NVMe cluster. 三節點 NVMe 叢集約 460 TB 可用容量。
Storage Server Storage Server
Phison's distributed Storage Server unifies Block, File, and S3 Object access on a single NVMe cluster — eliminating storage silos and delivering enterprise-grade resilience for AI and hybrid workloads. 群聯分散式儲存平台在單一 NVMe 叢集上統一 Block、File、S3 存取，消除儲存孤島，為 AI 與混合工作負載提供企業級韌性。
~ ~ 0 0 GB/s GB/s Read Throughput 讀取吞吐量
100Gb network and Pascari NVMe SSDs deliver aggregate read bandwidth for AI datasets. 100Gb 網路與 Pascari NVMe SSDs 為 AI 資料集提供聚合讀取頻寬。
~ ~ 100 100 K K IOPS 隨機讀取
Block, File, and S3 Object access on a single cluster — no storage silos. 單一叢集同時支援 Block、File、S3 存取，消除儲存孤島。
Core Barriers in Enterprise Storage Infrastructure 企業儲存基礎設施的核心障礙
Organizations building AI infrastructure encounter fundamental storage challenges that slow deployment and increase total cost of ownership.建構 AI 基礎設施的組織面臨根本性儲存挑戰，拖慢部署速度並增加總擁有成本。
Different Storage Needs for Every Use Case 每種使用情境需要不同儲存
AI training, inferencing, databases, and file workloads each demand different storage protocols — Block, File, and Object — forcing organizations to maintain separate storage silos. AI 訓練、推論、資料庫和檔案工作負載各自需要不同的儲存協定 — Block、File 和 Object — 迫使企業維護獨立的儲存孤島。
Cost Balancing a Mix of Data Tiers 多層資料成本難以平衡
Balancing hot NVMe performance storage with cold archive tiers is complex. Organizations overprovision or underutilize expensive SSD capacity due to lack of unified visibility. 在高效能 NVMe 與冷資料層間取得平衡十分複雜，缺乏統一可視性導致過度配置或浪費。
Challenges Supporting Enterprise Migration 企業遷移困難重重
Migrating from legacy SAN/NAS to modern distributed storage requires downtime windows, data migration plans, and retraining of IT staff — delaying AI projects. 從舊有 SAN/NAS 遷移至現代分散式儲存需要停機視窗、資料搬遷計畫與人員再訓練，拖延 AI 專案。
Growing IT Bottlenecks for AI Workloads AI 工作負載的 IT 瓶頸日增
As GPU clusters scale, storage bandwidth and IOPS requirements grow non-linearly. Traditional storage architectures cannot keep up with the throughput demands of LLM training. GPU 叢集擴增時，儲存頻寬與 IOPS 需求非線性增長，傳統架構無法跟上 LLM 訓練吞吐量需求。
One Rich Hardware Profile, One Rich Access Mode 單一硬體架構，單一存取模式
Vendor lock-in forces teams to use proprietary access APIs, making it impossible to serve Kubernetes CSI, NFS, and S3 workloads from a single unified storage platform. 供應商鎖定迫使團隊使用專有 API，無法從單一統一儲存平台同時服務 K8s CSI、NFS 與 S3 工作負載。
Broad Data Backup and Disaster Recovery 資料備份與災難復原範圍廣泛
Enterprise storage must provide snapshot, replication, and EC redundancy. Legacy systems require separate appliances for each function, increasing operational overhead. 企業儲存須提供快照、複寫與 EC 冗餘，傳統系統每項功能需獨立設備，增加營運負擔。
Storage System Architecture 儲存系統架構
Three Access Modes, One Unified Storage Platform 三種存取模式，一個統一儲存平台
Storage Server converges Block, File, and Object storage onto a single cluster — eliminating silos without sacrificing performance or protocol fidelity. 群聯儲存伺服器將 Block、File、Object 儲存整合至單一叢集，消除孤島而不犧牲效能或協定保真度。
- VM · K8s CSI · DB VM · K8s CSI · 資料庫
- [ Install Storage Agent ] [ 安裝 Storage Agent ]
- Linux App Linux 應用程式
- [ Install Storage Agent ] [ 安裝 Storage Agent ]
- External Clients via HTTPS Access 外部客戶端 HTTPS 存取
- [ Protocol Required Only ] [ 僅需協定支援 ]
Storage Node 1 儲存節點 1
Storage Node 2 儲存節點 2
Storage Node 3 儲存節點 3
3 nodes 節點 10 drives 顆磁碟 15.36 TB per drive 每顆 ~460 TB Raw Capacity 原始容量
100Gb 100Gb NIC NIC ~20 GB/s ~20 GB/s Read 讀取 ~8 GB/s ~8 GB/s Write 寫入 ~33K ~33K IOPS (4K rand read) IOPS (4K 隨機讀)
- Auto Rebalancing 自動重平衡
- Zero Downtime SSD / Node Scale-out 零停機 SSD / 節點擴充
- Rack Failure Recovery 機架故障復原
- Host Failure Recovery 主機故障復原
- SSD Failure Recovery SSD 故障復原
- Web-based Resource Management Interface 網頁式資源管理介面
- Block Data Access Block 資料存取
- File Data Access File 資料存取
- Object Data Access Object 資料存取
- Snapshot 快照
- Disaster Recovery 災難復原
- Data Encryption 資料加密
Block Raw Device 區塊裸裝置
VMK8s CSIDB
Delivers raw block access with consistent low-latency IOPS for databases, virtual machines, and Kubernetes persistent volumes. 為資料庫、虛擬機和 Kubernetes 持續磁碟卷 (Persistent Volumes) 提供具備穩定低延遲 IOPS 的原始區塊存取 (Raw Block Access)。
Standard File Access 標準檔案存取
Linux AppNFSSMB
POSIX-compliant distributed file system. Supports NFS v3/v4.1 and SMB 3.x protocols for seamless integration with existing Linux and Windows applications. 符合 POSIX 標準的分散式檔案系統。支援 NFS v3/v4.1 與 SMB 3.x 協定，能無縫整合現有的 Linux 和 Windows 應用程式。
S3 Object Storage S3 物件儲存
External ClientsHTTPS
AWS S3-compatible API for AI training datasets, model artifacts, and application data. Accessible from anywhere via standard HTTPS without additional agents. 相容於 AWS S3 的 API，適用於 AI 訓練資料集、模型構件 (Artifacts) 和應用程式資料。可從任何地方透過標準 HTTPS 存取，無需安裝額外代理程式。
Core Storage Technology 核心儲存技術
The storage platform is designed from the ground up for enterprise AI workloads, combining hardware-level SSD optimization with software-defined distributed storage.儲存平台從底層為企業 AI 工作負載設計，結合硬體級 SSD 優化與軟體定義分散式儲存。
EC 2+1 Erasure Coding Protection EC 2+1 抹除碼保護
Two-plus-one erasure coding tolerates simultaneous SSD and node failures with automatic rebuild. Data durability at 66% usable efficiency — superior to 3-way replication. EC 2+1 抹除碼技術容許 SSD 與節點同時發生故障並執行自動重建。資料耐久度高，且具備 66% 的可用容量效率，優於傳統的 3 份複寫 (3-way replication)。
Automatic Failure Domain Rebalancing 故障網域自動平衡
Hot-add SSDs or storage nodes and the platform automatically redistributes data across the expanded cluster with zero downtime and zero manual intervention. 熱插拔新增 SSD 或儲存節點，平台會自動在擴充後的叢集中重新分配資料，實現零停機時間與零人工干預。
Unified External Plane 統一外部平面
A single storage cluster serves Block, File, and S3 workloads simultaneously with per-volume policy controls for IOPS limits, snapshot schedules, and replication targets. 單一儲存叢集可同時服務 Block、File 和 S3 工作負載，並提供每個儲存卷 (Volume) 的原則控制，包括 IOPS 限制、快照排程與複寫目的地。
Cache-Tiered Caching 分層快取機制
Intelligent flash-to-flash caching accelerates hot data access. Phison NVMe SSD firmware optimization ensures consistent latency under heavy mixed read/write workloads. 智慧型的 Flash-to-Flash 快取加速熱資料存取。群聯 NVMe SSD 韌體優化可確保在繁重混合讀寫工作負載下的穩定延遲。
aiDAPTIV Cache Memory aiDAPTIV 快取記憶體
Optional flash-based KV cache tier extends storage bandwidth for AI inference workloads, reducing GPU idle time caused by I/O-bound data loading. 可選配的 Flash-based KV 快取層可擴展 AI 推論工作負載的儲存頻寬，減少因 I/O 受限資料載入所導致的 GPU 閒置時間。
Capacity Planning & SSD Management 容量規劃與 SSD 管理
Web-based dashboard provides real-time IOPS, throughput, latency, and capacity metrics. Predictive capacity planning alerts before utilization thresholds are breached. 網頁式儀表板提供即時的 IOPS、吞吐量、延遲與容量指標。預測性容量規劃會在達到使用率閾值前發出警報。