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This article details the evolution of Baidu's Sugar BI platform, highlighting its AI‑driven analytics, extensive data source support, zero‑code visual design, smart chart recommendation, and the conversational Sugar Bot that transforms natural‑language queries into actionable visual insights.
With AI training demands outgrowing single‑chip GPU clusters, this article explains how to construct and speed up heterogeneous AI clusters—combining GPUs, Kunlun, and Ascend chips—by addressing interconnect, distributed parallel strategies, and specialized acceleration suites to achieve high MFU and efficient large‑model training.
At QCon 2024, Baidu Intelligent Cloud presented the complexities of optimizing diverse CPU architectures in data centers and introduced Btune, a one‑click solution that automates bottleneck detection, analysis, and performance tuning across Intel, AMD, and ARM platforms, enabling engineers to boost service efficiency.
Baidu’s Collective Communication Library (BCCL) enhances large‑model distributed training by improving real‑time bandwidth monitoring, fault diagnosis, network stability, and performance, leveraging RDMA networks and GPU‑specific optimizations to increase effective training time to 98% and bandwidth utilization to 95%.
This article details Baidu Intelligent Cloud's database operations team’s end‑to‑end design of an AI‑driven knowledge‑base Q&A system, covering background, architecture, technical choices, module implementation, key challenges such as vector‑search recall and token limits, and real‑world deployment scenarios.
This article explains how Baidu Cloud’s Btune performance‑diagnostic tool helps identify CPU, memory and NUMA bottlenecks, provides automatic optimization suggestions, and demonstrates a real‑world test that improves a memory‑intensive program’s runtime by up to 36.8% after applying the recommended changes.
This article details Baidu Cloud's BTS semi‑structured storage system, covering its three‑generation evolution, three‑layer architecture, performance optimizations, high‑availability mechanisms, and real‑world use cases such as autonomous driving and large‑scale system monitoring.
This article examines the rapid growth of China's database market, the technical hurdles of moving databases to public cloud—including engine selection, lengthy migration processes, efficiency, disaster recovery, and data consistency—and explains how Baidu Intelligent Cloud's DTS platform offers a smooth, reliable, high‑availability, and high‑performance one‑stop solution with real‑world use cases.
This article examines the challenges of legacy mainframe‑based banking core systems, explains why banks are shifting to general‑purpose servers, outlines the distributed architecture and database requirements, and showcases GaiaDB‑X’s multi‑layer design and real‑world financial deployments.
GaiaDB, Baidu’s cloud‑native database, combines compute‑storage separation with a fused, log‑service architecture to boost performance, simplify consistency, and deliver multi‑level high availability across zones and regions, while supporting new features such as parallel query, HTAP replicas, and serverless scaling.
