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Latest from DeWu Technology

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DeWu Technology

Feb 26, 2025 · Backend Development

Migrating to Rust: A Case Study in High-Performance Computing

Migrating a Java computing layer to Rust yielded dramatic performance gains—30% lower CPU usage, 70% less memory—and greater stability, as the authors explain how Rust’s ownership, borrowing, lifetimes, and concurrency, combined with optimized data handling, FFI integration, Tokio async, Docker deployment, and monitoring, outweigh the steep learning curve and ecosystem gaps.

Backend DevelopmentFFIHigh Performance Computing

0 likes · 22 min read

Migrating to Rust: A Case Study in High-Performance Computing

DeWu Technology

Feb 24, 2025 · Mobile Development

Design and Implementation of a Mini‑Program Management Platform

The DeWu mini‑program platform unifies WeChat, Alipay and other channels into a single workflow by providing role‑based management, cross‑platform API abstraction, real‑time data synchronization, and Feishu‑linked approval, reducing manual tasks, speeding complaint handling, and boosting operational efficiency while addressing integration and security challenges.

AI toolsMiniProgramOperations

0 likes · 9 min read

Design and Implementation of a Mini‑Program Management Platform

DeWu Technology

Feb 19, 2025 · Artificial Intelligence

Scenario-aware Multi-Scenario Recommendation Models: SACN, SAINet, and DSWIN

The paper presents a comprehensive multi‑scenario recommendation study introducing three models—SACN, SAINet, and DSWIN—that integrate scene‑aware attention, attribute‑level preferences, and contrastive disentanglement to capture distinct user interests, achieving consistent AUC gains and online CTR improvements across real‑world datasets.

CTR predictioncontrastive learningdeep learning

0 likes · 43 min read

Scenario-aware Multi-Scenario Recommendation Models: SACN, SAINet, and DSWIN

DeWu Technology

Feb 17, 2025 · Artificial Intelligence

Optimizing Large Model Inference: High‑Performance Frameworks and Techniques

The article reviews high‑performance inference strategies for large language models such as Deepseek‑R1, detailing CPU‑GPU process separation, Paged and Radix Attention, Chunked Prefill, output‑length reduction, tensor‑parallel multi‑GPU scaling, and speculative decoding, each shown to markedly boost throughput and cut latency in real deployments.

AIGPU AccelerationSpeculative Decoding

0 likes · 22 min read

Optimizing Large Model Inference: High‑Performance Frameworks and Techniques

DeWu Technology

Feb 12, 2025 · Artificial Intelligence

Edge Intelligence for Intelligent Video Cover Recommendation

The article describes an edge‑based video‑cover recommendation system for DeWu that leverages the MNN SDK and a lightweight MobileNetV3 model, performing on‑device inference with quantization and parallel processing to automatically select high‑quality covers, achieving sub‑second latency and boosting click‑through rates by up to 18 %.

Edge AIInference OptimizationModel Deployment

0 likes · 12 min read

Edge Intelligence for Intelligent Video Cover Recommendation

DeWu Technology

Feb 10, 2025 · Operations

White‑Screen Operations Platform for Multi‑Cloud Kubernetes Middleware Management

The White‑Screen Operations Platform unifies multi‑cloud Kubernetes cluster and middleware management—automating Kafka, Elasticsearch, node, PV, and YAML tasks through a visual UI, eliminating fragmented command‑line scripts, cutting operation times from hours to minutes, standardizing processes, providing auditability, and delivering significant cost savings while scaling for future Kubernetes resources.

AutomationKubernetesObservability

0 likes · 20 min read

White‑Screen Operations Platform for Multi‑Cloud Kubernetes Middleware Management

DeWu Technology

Jan 22, 2025 · Operations

How We Cut Video Detection Memory Usage by 78% with WebAssembly and WorkerFS

This article details the challenges of video corruption detection on a creator platform, analyzes existing server‑side and client‑side approaches, and presents a WebAssembly‑based solution using ffmpeg, WorkerFS, and memory‑growth tuning that reduces memory consumption by up to 78% while speeding up large‑file processing.

Memory OptimizationPerformanceVideo processing

0 likes · 13 min read

How We Cut Video Detection Memory Usage by 78% with WebAssembly and WorkerFS

DeWu Technology

Jan 20, 2025 · Backend Development

Migrating Observability Compute Layer from Java to Rust: Ownership, Concurrency, Deployment, and Monitoring

The article details how moving a high‑throughput observability compute layer from Java to Rust—leveraging Rust’s ownership, zero‑cost async, and static binary deployment—cut memory usage by roughly 68%, CPU consumption by 40%, while outlining monitoring setup, concurrency model, and the steep learning‑curve challenges.

DeploymentObservabilityRust

0 likes · 18 min read

Migrating Observability Compute Layer from Java to Rust: Ownership, Concurrency, Deployment, and Monitoring

DeWu Technology

Jan 13, 2025 · Artificial Intelligence

Unlock GPU Power: A Hands‑On Triton Guide for Vector Add, Matrix Multiply & RoPE

This article introduces Triton—a Python‑based GPU programming language—covers essential GPU architecture, walks through practical kernels for vector addition, matrix multiplication, and rotary position encoding, compares performance with PyTorch, and provides debugging tips for high‑performance deep‑learning workloads.

CUDAGPU programmingPerformance Optimization

0 likes · 22 min read

Unlock GPU Power: A Hands‑On Triton Guide for Vector Add, Matrix Multiply & RoPE

DeWu Technology

Jan 6, 2025 · Artificial Intelligence

Design and Implementation of a Retrieval‑Augmented Generation (RAG) Answering Assistant for the Dewu Open Platform

The paper describes building a Retrieval‑Augmented Generation assistant for the Dewu Open Platform that leverages GPT‑4o‑mini, OpenAI embeddings, Milvus vector store, and LangChain.js to semantically retrieve API documentation, structure user queries, and generate accurate, JSON‑formatted answers, thereby reducing manual support and hallucinations.

AILLMLangChain

0 likes · 28 min read

Design and Implementation of a Retrieval‑Augmented Generation (RAG) Answering Assistant for the Dewu Open Platform