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Latest from Baidu Intelligent Cloud Tech Hub

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Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Dec 10, 2025 · Artificial Intelligence

Accelerate LLM Deployment on Baidu Kunlun XPU with the Open‑Source vLLM‑Kunlun Plugin

The vLLM‑Kunlun Plugin, built on the vLLM hardware‑plugin RFC, lets developers deploy any major large language model on Baidu's Kunlun XPU instantly without modifying vLLM core code, dramatically shortening migration time, providing high‑performance fusion operators, and offering open‑source tools for precision verification and profiling.

KunlunLLMOpen Source
0 likes · 8 min read
Accelerate LLM Deployment on Baidu Kunlun XPU with the Open‑Source vLLM‑Kunlun Plugin
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Dec 4, 2025 · Artificial Intelligence

How Offloading Latent Cache to CPU Boosts DeepSeek‑V3.2‑Exp Decoding Throughput

This report details the analysis of memory bottlenecks in DeepSeek‑V3.2‑Exp, proposes the Expanded Sparse Server (ESS) that offloads latent cache to CPU memory, and demonstrates through high‑fidelity simulation that the approach, combined with cache‑warmup and overlap techniques, can double decoding throughput for long‑context inference.

Cache offloadGPU‑CPU optimizationLLM inference
0 likes · 21 min read
How Offloading Latent Cache to CPU Boosts DeepSeek‑V3.2‑Exp Decoding Throughput
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Nov 25, 2025 · Artificial Intelligence

Why DeepSeek‑V3.2‑Exp Lost Performance and How a Simple RoPE Fix Restored It

The Baidu Baige team discovered that DeepSeek‑V3.2‑Exp’s long‑context performance lagged behind the official report, traced the issue to a subtle RoPE layout mismatch in the open‑source inference demo, collaborated with DeepSeek to fix it, and verified that the model’s speed and accuracy fully recovered across multiple benchmarks.

AI infrastructureDeepSeekLLM inference
0 likes · 9 min read
Why DeepSeek‑V3.2‑Exp Lost Performance and How a Simple RoPE Fix Restored It
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Nov 20, 2025 · Artificial Intelligence

Boost Multimodal Model Training Efficiency with Offline Sequence Packing and Mixed‑Modality Data

Baidu's Baige team introduces an extended multimodal data loader, automated ShareGPT format conversion, and offline sequence packing techniques that together double token throughput, cut SFT training time by up to six times, and improve GPU utilization and stability for large vision‑language models.

AI infrastructureAIAKGPU efficiency
0 likes · 7 min read
Boost Multimodal Model Training Efficiency with Offline Sequence Packing and Mixed‑Modality Data
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Nov 19, 2025 · Artificial Intelligence

Boost LLM Inference Speed with Token‑Level Two‑Chunk Overlap

Token‑level Two‑Chunk Overlap replaces traditional batch‑level Two‑Batch Overlap, dynamically splitting sequences into balanced token chunks, enabling near‑equal compute and communication times, improving GPU utilization and achieving up to 30% throughput gains in heterogeneous request workloads, with zero accuracy loss.

Batch schedulingGPU utilizationLLM inference
0 likes · 9 min read
Boost LLM Inference Speed with Token‑Level Two‑Chunk Overlap
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Nov 10, 2025 · Cloud Computing

How Polar‑TCP Breaks Kernel Network Bottlenecks for Million‑IOPS Cloud Services

This article explains how traditional kernel network stacks struggle with modern cloud data‑center workloads and introduces Baidu Intelligent Cloud's Polar solution—Polar‑TCP and Polar‑RDMA—which combine user‑space DPDK drivers, a lightweight TCP stack, and an industrial‑grade RPC framework to achieve near‑RDMA performance while preserving ecosystem compatibility.

Cloud ComputingDPDKHigh‑Performance Networking
0 likes · 24 min read
How Polar‑TCP Breaks Kernel Network Bottlenecks for Million‑IOPS Cloud Services
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Nov 7, 2025 · Artificial Intelligence

From Big Data to 30,000‑GPU Clusters: The Evolution of China’s AI Infrastructure

In a deep interview, Baidu AI Computing chief scientist Wang Yanpeng and host Koji trace China's internet infrastructure from the early big‑data era through cloud computing to today's AI boom, highlighting the pivotal role of compute power, GPU acceleration, data scaling, and Baidu's Baige platform in shaping the AI arms race.

AI infrastructureBaidu BaigeCloud Computing
0 likes · 26 min read
From Big Data to 30,000‑GPU Clusters: The Evolution of China’s AI Infrastructure
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Nov 4, 2025 · Artificial Intelligence

How Baidu’s Baige Accelerates Multimodal Video Training with Context Parallelism

Baidu Baige’s enhanced veRL framework dramatically boosts video frame rates and resolution limits, cuts training time, reduces memory usage, and improves model accuracy by leveraging context parallelism and optimized attention on Ampere GPUs for multimodal mixed‑training scenarios.

AI accelerationContext ParallelismVideo processing
0 likes · 6 min read
How Baidu’s Baige Accelerates Multimodal Video Training with Context Parallelism
Baidu Intelligent Cloud Tech Hub
Baidu Intelligent Cloud Tech Hub
Oct 29, 2025 · Operations

How to Prevent Avalanche Failures in Large‑Scale Microservice Systems

This article explains how Baidu's SRE team identified the root causes of avalanche failures in massive microservice architectures, modeled system limits with Little’s Law, and implemented engineering practices such as retry budgets, queue throttling, and global TTL controls to achieve self‑healing and eliminate avalanche incidents.

MicroservicesSREavalanche failure
0 likes · 9 min read
How to Prevent Avalanche Failures in Large‑Scale Microservice Systems