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600 articles · Page 5 of 6
Architects' Tech Alliance
Architects' Tech Alliance
Jun 14, 2023 · Artificial Intelligence

AI Compute Landscape: GPUs, Network, and Storage as Core Engines

The article analyzes how large language models like ChatGPT are reshaping the software ecosystem by positioning AI compute—driven by GPUs, high‑speed networking, and advanced storage solutions such as HBM and 3D‑stacked memory—as the foundational engine for future information systems, highlighting current market trends and technical challenges.

AIComputeHardware
0 likes · 4 min read
AI Compute Landscape: GPUs, Network, and Storage as Core Engines
Python Programming Learning Circle
Python Programming Learning Circle
Jun 13, 2023 · Fundamentals

Python Performance Optimization Tools and Techniques

This article introduces a variety of Python optimization tools—including NumPy, SciPy, Pandas, JIT compilers like PyPy, GPU libraries, Cython, Numba, and interfacing utilities—explaining how they can make code more concise, faster, and better suited for single‑processor or multi‑processor execution.

LibrariesPerformancePython
0 likes · 8 min read
Python Performance Optimization Tools and Techniques
Ctrip Technology
Ctrip Technology
Jun 8, 2023 · Frontend Development

Optimizing CSS Animation Performance: Techniques and Best Practices

This article explains how to improve CSS animation performance by understanding the browser rendering pipeline, using GPU‑accelerated transforms, avoiding costly properties and complex selectors, leveraging will‑change and requestAnimationFrame, and preferring CSS over JavaScript for smoother, lower‑latency visual effects.

CSSOptimizationPerformance
0 likes · 13 min read
Optimizing CSS Animation Performance: Techniques and Best Practices
Architects' Tech Alliance
Architects' Tech Alliance
Jun 1, 2023 · Fundamentals

Overview of the Xinchuang (Information Technology Innovation) Industry: CPU, GPU, and Storage Fundamentals

This article provides a comprehensive overview of the Xinchuang industry, detailing the fundamental concepts, architectures, and classifications of CPUs, GPUs, and storage devices, and explains how these core hardware components support the goal of achieving self‑controlled, secure information technology in China.

CPUHardwareStorage
0 likes · 6 min read
Overview of the Xinchuang (Information Technology Innovation) Industry: CPU, GPU, and Storage Fundamentals
Open Source Linux
Open Source Linux
May 29, 2023 · Fundamentals

What Is a GPU? Understanding Its Role in Graphics, AI, and Computing

This article explains what a GPU (Graphics Processing Unit) is, how it differs from a CPU, its architecture and performance characteristics, and why it powers everything from real‑time rendering to AI inference, using examples like the NVIDIA RTX 3090.

CPU comparisonGraphics Processing UnitNVIDIA RTX 3090
0 likes · 8 min read
What Is a GPU? Understanding Its Role in Graphics, AI, and Computing
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
May 29, 2023 · Artificial Intelligence

How PAI‑Blade Supercharges Stable Diffusion Inference on GPUs

This article explains how PAI‑Blade, built on the BladeDISC compiler and BlaDNN library, dramatically reduces latency and memory usage for Stable Diffusion inference, provides step‑by‑step usage examples with code, shows performance gains on A100 and A10 GPUs, and outlines future optimization directions.

Inference OptimizationPAI-Bladegpu
0 likes · 9 min read
How PAI‑Blade Supercharges Stable Diffusion Inference on GPUs
Tencent Cloud Developer
Tencent Cloud Developer
May 24, 2023 · Artificial Intelligence

Deploying Stable Diffusion on Tencent Cloud: A Step‑by‑Step Guide

Deploy Stable Diffusion on Tencent Cloud by building a Docker image, pushing it to TCR, creating a GPU‑enabled TKE cluster with CFS storage, configuring qGPU sharing, exposing the service via Cloud Native API Gateway, optimizing inference with TACO Kit, storing results in COS, and applying content moderation.

AI DeploymentKubernetesStable Diffusion
0 likes · 19 min read
Deploying Stable Diffusion on Tencent Cloud: A Step‑by‑Step Guide
JD Retail Technology
JD Retail Technology
May 18, 2023 · Artificial Intelligence

Local Deployment, Inference, and Fine‑tuning of the Vicuna‑7B Large Language Model

This article details the step‑by‑step process of preparing the environment, merging weights, installing dependencies, running inference, evaluating Vicuna‑7B against other models, and attempting fine‑tuning, while highlighting performance results, encountered issues, and future work for large language model deployment.

Fine-tuningVicunagpu
0 likes · 11 min read
Local Deployment, Inference, and Fine‑tuning of the Vicuna‑7B Large Language Model
JD Retail Technology
JD Retail Technology
May 16, 2023 · Artificial Intelligence

Deploying and Fine‑Tuning the Alpaca‑LoRA Large Language Model on a Multi‑GPU Server

This guide details the end‑to‑end process of installing GPU drivers, setting up a Python environment, deploying the open‑source Alpaca‑LoRA model, fine‑tuning it with Chinese data on a multi‑GPU server, and performing inference, while highlighting practical challenges and performance observations.

Alpaca-LoRAFine-tuningLLM
0 likes · 11 min read
Deploying and Fine‑Tuning the Alpaca‑LoRA Large Language Model on a Multi‑GPU Server
ByteDance SYS Tech
ByteDance SYS Tech
May 12, 2023 · Fundamentals

Inside Intel GPU Render Engine: How 3D Rendering Works at the Hardware Level

This article explains the architecture and workflow of Intel's GPU render engine, covering the 3D pipeline, command streamer, fixed‑function units, execution units, URB handling, thread dispatch, shader stages, sampler state, and the Mesa driver implementation that translates OpenGL commands into hardware instructions.

Graphics PipelineIntelMesa
0 likes · 39 min read
Inside Intel GPU Render Engine: How 3D Rendering Works at the Hardware Level
Architects' Tech Alliance
Architects' Tech Alliance
May 11, 2023 · Fundamentals

Overview of ARM Processor Architectures and Their Evolution

This article provides a comprehensive overview of ARM's processor architectures—including the A, R, and M profiles—detailing the evolution of major Cortex‑A series CPUs, the big.LITTLE concept, and the Mali GPU families, while also offering references to related technical reports and resources.

ARMCPUCortex
0 likes · 13 min read
Overview of ARM Processor Architectures and Their Evolution
Alibaba Cloud Native
Alibaba Cloud Native
Apr 24, 2023 · Artificial Intelligence

Deploy Stable Diffusion WebUI on Alibaba Cloud Function Compute in One Command

This guide walks you through deploying the open‑source Stable Diffusion WebUI on Alibaba Cloud Function Compute using Serverless Devs, covering prerequisites, a single‑line deployment command, configuration details, access URL, and practical tips for handling GPU rendering and cold‑start latency.

AI DeploymentFunction ComputeServerless
0 likes · 5 min read
Deploy Stable Diffusion WebUI on Alibaba Cloud Function Compute in One Command
Top Architect
Top Architect
Apr 21, 2023 · Artificial Intelligence

Fine‑Tuning LLaMA‑7B with Alpaca‑LoRA to Build a Chinese ChatGPT

This article explains why and how to fine‑tune the LLaMA‑7B model using the cheap Alpaca‑LoRA approach, covering hardware requirements, dataset preparation, LoRA training, optional model merging and quantization, and provides ready‑to‑run code snippets for single‑ and multi‑GPU setups.

Alpaca-LoRAFine-tuningLLM
0 likes · 10 min read
Fine‑Tuning LLaMA‑7B with Alpaca‑LoRA to Build a Chinese ChatGPT
Alibaba Cloud Native
Alibaba Cloud Native
Apr 18, 2023 · Artificial Intelligence

How to Deploy a CPU‑Based Stable Diffusion Service on Alibaba Cloud ACK

This guide walks you through the prerequisites, step‑by‑step console and kubectl procedures, YAML configuration, and post‑deployment verification needed to run a CPU‑only Stable Diffusion model on Alibaba Cloud Container Service (ACK) and optionally switch to a GPU‑enabled version.

ACKAI Model DeploymentCPU
0 likes · 7 min read
How to Deploy a CPU‑Based Stable Diffusion Service on Alibaba Cloud ACK
ByteFE
ByteFE
Apr 12, 2023 · Frontend Development

Design and Refactoring of the xGis 3D Map Event System and Picking Engine

This article details the background, problems, and comprehensive refactoring plan for the xGis web‑based 3D map library, covering event classification, API design, layer interaction proxy, CPU/GPU picking implementations, performance trade‑offs, and future optimization directions.

3D mappingCPUJavaScript
0 likes · 22 min read
Design and Refactoring of the xGis 3D Map Event System and Picking Engine
Architects' Tech Alliance
Architects' Tech Alliance
Mar 29, 2023 · Fundamentals

Stream Multiprocessor (SM) Architecture and Execution Pipeline in GPUs

This article provides a comprehensive overview of GPU stream multiprocessors, detailing their micro‑architecture, instruction fetch‑decode‑execute pipeline, SIMT/ SIMD organization, warp scheduling, scoreboard mechanisms, and techniques for handling thread divergence and deadlock in GPGPU designs.

SIMTScoreboardStream Multiprocessor
0 likes · 16 min read
Stream Multiprocessor (SM) Architecture and Execution Pipeline in GPUs
DataFunSummit
DataFunSummit
Mar 12, 2023 · Artificial Intelligence

PaddleBox and FeaBox: GPU‑Based Large‑Scale Sparse Model Training and Integrated Feature Extraction Frameworks at Baidu

The article introduces PaddleBox and FeaBox, two GPU‑driven frameworks designed for massive sparse DNN training and unified feature extraction, detailing their architecture, performance advantages, hardware‑software co‑design challenges, and successful deployment across Baidu's advertising systems.

FeaBoxPaddleBoxfeature extraction
0 likes · 24 min read
PaddleBox and FeaBox: GPU‑Based Large‑Scale Sparse Model Training and Integrated Feature Extraction Frameworks at Baidu
Baidu Geek Talk
Baidu Geek Talk
Feb 17, 2023 · Artificial Intelligence

How PGLBox Achieves 27× Faster GPU‑Powered Large‑Scale Graph Learning

PGLBox, Baidu’s GPU‑based large‑scale graph training framework, delivers up to 27× speedup over CPU clusters by fully GPU‑accelerating storage, sampling, and training, supporting billions of nodes, advanced GNN algorithms, multi‑level storage, and seamless integration of massive pretrained models.

Distributed ComputingGraph Neural NetworksLarge‑Scale Training
0 likes · 7 min read
How PGLBox Achieves 27× Faster GPU‑Powered Large‑Scale Graph Learning
Meituan Technology Team
Meituan Technology Team
Feb 9, 2023 · Backend Development

Efficient Deployment Architecture for Visual Inference Services: GPU Utilization Optimization

Meituan Visual's engineering team tackled the common low‑GPU‑utilization bottleneck in online inference services by splitting model structures and adopting micro‑service deployment, raising GPU usage from 40% to 100% and more than tripling QPS, and then generalized the approach for other GPU‑based services.

MicroservicesPerformance OptimizationTensorRT
0 likes · 21 min read
Efficient Deployment Architecture for Visual Inference Services: GPU Utilization Optimization
Architects' Tech Alliance
Architects' Tech Alliance
Jan 27, 2023 · Artificial Intelligence

Challenges and Future Directions of GPU in AI Computing: A Comparison with TPU and FPGA

The article analyzes how GPUs, once dominant in accelerating AI workloads, now face limitations in precision, energy efficiency, and on‑chip networking, prompting a shift toward specialized accelerators like Google's TPU and FPGA solutions, while also exploring emerging GPU‑friendly scenarios such as VR/AR, cloud gaming, and military applications.

FPGATPUVR/AR
0 likes · 11 min read
Challenges and Future Directions of GPU in AI Computing: A Comparison with TPU and FPGA
DataFunSummit
DataFunSummit
Jan 5, 2023 · Artificial Intelligence

GPU Acceleration Techniques for Large AI Models: Parallelism, Fusion, and Simplification

These notes explain how GPUs address the massive data, serial dependencies, and high computational complexity of modern AI by employing three acceleration strategies—parallelism, operator fusion, and simplification—illustrated with Megatron-LM, MoE models, and practical compression techniques such as quantization, distillation, and pruning.

AIMegatronParallelism
0 likes · 16 min read
GPU Acceleration Techniques for Large AI Models: Parallelism, Fusion, and Simplification
DataFunTalk
DataFunTalk
Jan 4, 2023 · Artificial Intelligence

GPU Acceleration Techniques for Large AI Models: Parallelism, Fusion, and Simplification

This article explains how GPUs address the massive data, serial dependencies, and high computational complexity of modern AI by employing three acceleration strategies—parallelism, operator fusion, and simplification—detailing methods such as model, pipeline, and tensor parallelism, Megatron framework, MoE models, and various model compression techniques.

AIMegatronParallelism
0 likes · 17 min read
GPU Acceleration Techniques for Large AI Models: Parallelism, Fusion, and Simplification
Python Programming Learning Circle
Python Programming Learning Circle
Dec 17, 2022 · Fundamentals

Accelerating Python Code with Taichi: Prime Counting, LCS, and Reaction‑Diffusion Examples

This article demonstrates how importing the Taichi library into Python can dramatically accelerate compute‑intensive tasks, showcasing prime counting, longest common subsequence, and reaction‑diffusion simulations with speedups up to 120× and GPU support, while providing installation and usage guidance.

PythonTaichidynamic programming
0 likes · 6 min read
Accelerating Python Code with Taichi: Prime Counting, LCS, and Reaction‑Diffusion Examples
Architects' Tech Alliance
Architects' Tech Alliance
Dec 11, 2022 · Fundamentals

Fundamentals of CPU, GPU, and Storage in the Xinchuang Industry

This article provides a comprehensive overview of the Xinchuang industry’s hardware fundamentals, detailing CPU architecture and operation, instruction set classifications, GPU concepts and workflows, storage categories, and the distinction between independent and integrated GPUs, while also noting related promotional resources.

CPUHardwareStorage
0 likes · 8 min read
Fundamentals of CPU, GPU, and Storage in the Xinchuang Industry
Architects' Tech Alliance
Architects' Tech Alliance
Nov 29, 2022 · Artificial Intelligence

In‑Depth Overview of NVIDIA Grace Hopper Superchip Architecture

The article provides a comprehensive technical overview of NVIDIA's Grace Hopper Superchip, detailing its heterogeneous CPU‑GPU design, high‑bandwidth NVLink‑C2C interconnect, performance advantages for HPC and AI workloads, programming model, and the architectural innovations that enable unprecedented scalability and productivity.

AICPUGrace Hopper
0 likes · 15 min read
In‑Depth Overview of NVIDIA Grace Hopper Superchip Architecture
Tencent Cloud Developer
Tencent Cloud Developer
Nov 29, 2022 · Game Development

GPU Rendering Pipeline and Hardware Architecture Overview

The article surveys GPU rendering pipelines and hardware architectures for desktop and mobile, explains classic stages, compares Immediate Mode, Tile‑Based and Tile‑Based Deferred rendering, details PowerVR, Mali and Adreno components, and offers optimization advice on draw calls, depth pre‑passes, shader efficiency, and render ordering.

GraphicsMobile GPUPerformance Optimization
0 likes · 66 min read
GPU Rendering Pipeline and Hardware Architecture Overview
Architects' Tech Alliance
Architects' Tech Alliance
Nov 7, 2022 · Artificial Intelligence

FastDeploy: One-Click AI Model Deployment Across GPUs, CPUs, and Edge Devices

FastDeploy is an open‑source toolkit that standardizes AI model APIs and enables developers to deploy vision, NLP, and speech models on diverse hardware—including GPUs, CPUs, Jetson, ARM, and various NPUs—using just three lines of code or a single command, while delivering end‑to‑end performance optimizations.

AI DeploymentCPUFastDeploy
0 likes · 11 min read
FastDeploy: One-Click AI Model Deployment Across GPUs, CPUs, and Edge Devices
Architects' Tech Alliance
Architects' Tech Alliance
Nov 1, 2022 · Databases

2022 China Database Industry Report: Emerging Hardware and Architectural Innovations

The September 2022 China Database Industry Analysis report highlights a wave of hardware‑driven innovations—including multi‑core CPUs, heterogeneous GPUs/TPUs/DPU, programmable FPGAs, CXL‑DDR5, persistent memory, NVMe‑oF, and RDMA‑based storage—that enable massive data storage and high‑concurrency real‑time computing across a range of novel database architectures and products.

OLTPdatabasesdistributed indexing
0 likes · 10 min read
2022 China Database Industry Report: Emerging Hardware and Architectural Innovations
Baidu Geek Talk
Baidu Geek Talk
Oct 31, 2022 · Artificial Intelligence

PaddleBox: A GPU‑Based Ultra‑Large‑Scale Sparse DNN Training Framework

PaddleBox is Baidu’s GPU‑based ultra‑large‑scale sparse DNN training framework that combines a three‑tier hierarchical parameter server (SSD, DRAM, HBM) with pipelined scheduling and multi‑machine multi‑GPU communication, delivering 5–40× cost‑performance gains over traditional CPU solutions and powering Baidu’s advertising services.

PaddleBoxSparse Parametersdeep learning
0 likes · 15 min read
PaddleBox: A GPU‑Based Ultra‑Large‑Scale Sparse DNN Training Framework
OPPO Kernel Craftsman
OPPO Kernel Craftsman
Oct 28, 2022 · Artificial Intelligence

ShaderNN: A GPU Shader‑Based Lightweight Inference Engine for Mobile AI Applications

ShaderNN is an open‑source, sub‑2 MB GPU‑shader inference engine that runs TensorFlow, PyTorch and ONNX models directly on mobile graphics textures via OpenGL fragment and compute shaders, delivering real‑time, low‑power AI for image‑heavy tasks while eliminating third‑party dependencies and achieving up to 90 % speed gains.

Inference EnginePerformanceShader
0 likes · 11 min read
ShaderNN: A GPU Shader‑Based Lightweight Inference Engine for Mobile AI Applications
Alibaba Cloud Native
Alibaba Cloud Native
Oct 10, 2022 · Cloud Native

What’s New in Koordinator v0.7? Enhanced Coscheduling, ElasticQuota, and Fine‑Grained GPU Sharing

Koordinator v0.7 adds major cloud‑native scheduling features—including enhanced gang (coscheduling) with Strict/NonStrict modes, multi‑hierarchy ElasticQuota management, fine‑grained GPU resource protocols, richer diagnostic APIs, and safer descheduling—targeting machine‑learning and big‑data workloads on Kubernetes.

CoschedulingElasticQuotaKubernetes
0 likes · 25 min read
What’s New in Koordinator v0.7? Enhanced Coscheduling, ElasticQuota, and Fine‑Grained GPU Sharing
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Sep 29, 2022 · Fundamentals

Understanding OpenGL Buffer Objects and VBO Optimization

This article explains the concept of OpenGL objects, focuses on common buffer objects such as VBO, VAO, and EBO, describes how they reduce CPU‑GPU transfer costs, and provides detailed code examples for creating, configuring, and rendering with Vertex Buffer Objects to improve graphics performance.

Buffer ObjectsOpenGLVBO
0 likes · 18 min read
Understanding OpenGL Buffer Objects and VBO Optimization
ELab Team
ELab Team
Sep 28, 2022 · Frontend Development

Master WebGL & Three.js: From Basics to 3D Rendering in the Browser

This article guides beginners through the fundamentals of computer graphics, explaining OpenGL, WebGL, GLSL, and the rendering pipeline, then demonstrates practical Three.js code for setting up scenes, cameras, lights, materials, and textures to create interactive 3D web experiences.

3D renderingGraphicsShader
0 likes · 20 min read
Master WebGL & Three.js: From Basics to 3D Rendering in the Browser
Architects' Tech Alliance
Architects' Tech Alliance
Sep 10, 2022 · Fundamentals

Overview of NVIDIA DOCA and SmartNIC/DPU Technologies

This article provides a comprehensive overview of NVIDIA's DOCA framework, BlueField DPU architecture, SDK components, programming models, and related technologies such as RDMA, RoCE, and GPUDirect RDMA, highlighting their roles in modern data‑center acceleration and security.

DOCADPURDMA
0 likes · 8 min read
Overview of NVIDIA DOCA and SmartNIC/DPU Technologies
NetEase Cloud Music Tech Team
NetEase Cloud Music Tech Team
Jul 6, 2022 · Industry Insights

Inside NetEase Cloud Music’s MLOps: Scaling AI with VK, ECI, and Ceph

This article details NetEase Cloud Music’s four‑layer machine‑learning platform architecture, covering resource provisioning with Visual Kubelet and Alibaba Cloud ECI, Ceph storage optimizations, TensorFlow migration, large‑scale graph neural network support, and end‑to‑end workflow tooling that together enable efficient, cost‑effective AI development and deployment.

CephGraph Neural NetworkKubernetes
0 likes · 24 min read
Inside NetEase Cloud Music’s MLOps: Scaling AI with VK, ECI, and Ceph
Youku Technology
Youku Technology
Jun 9, 2022 · Mobile Development

Design and Architecture of the Cross-Platform Multimedia Rendering Engine OPR

The OPR engine provides a cross‑platform, GPU‑accelerated rendering framework that unifies audio‑video pre‑ and post‑processing, native UI‑driven danmaku rendering, and real‑time visual effects such as human‑body recognition, using a modular command‑stream architecture, C++ core, monitoring tools, and extensibility for future Vulkan, VR, and plugin integration.

Native UIgpumultimedia rendering
0 likes · 15 min read
Design and Architecture of the Cross-Platform Multimedia Rendering Engine OPR
Youku Technology
Youku Technology
Jun 8, 2022 · Mobile Development

How Youku Achieves Real-Time Bullet‑Screen Pass‑Through on Mobile

This article details Youku's technical approach to rendering bullet‑screen pass‑through on mobile devices, covering cloud‑based and on‑device segmentation pipelines, GPU‑accelerated rendering steps, performance optimizations, and engineering challenges to deliver seamless immersive viewing.

Bullet ScreenMetalOpenGL
0 likes · 11 min read
How Youku Achieves Real-Time Bullet‑Screen Pass‑Through on Mobile
Shopee Tech Team
Shopee Tech Team
Jun 2, 2022 · Backend Development

Applying GPU Technology for High‑Throughput Image Rendering in Shopee Off‑Platform Ads

The Shopee Off‑Platform Ads team built a GPU‑accelerated Creative Rendering System that uses a four‑layer architecture, CGO‑bridged C/C++ kernels, and template caching to process billions of product images daily, achieving roughly ten‑fold speedup, half the cost, and far reduced rack space while handling high concurrency.

AdvertisingCUDAGo
0 likes · 23 min read
Applying GPU Technology for High‑Throughput Image Rendering in Shopee Off‑Platform Ads
Baidu Geek Talk
Baidu Geek Talk
May 30, 2022 · Mobile Development

Advanced OpenCL Optimization Techniques for Qualcomm Adreno GPUs on Mobile Devices

The article presents advanced OpenCL optimization techniques for Qualcomm Adreno mobile GPUs, explaining the programming model, profiling methods, bottleneck identification, and kernel‑level strategies such as fast math, fp16, vectorized memory accesses, and hardware‑specific features to improve compute‑ and memory‑bound performance on Android devices.

AdrenoMobile ComputingOpenCL
0 likes · 12 min read
Advanced OpenCL Optimization Techniques for Qualcomm Adreno GPUs on Mobile Devices
Architects' Tech Alliance
Architects' Tech Alliance
May 23, 2022 · Industry Insights

GPU Wars in the Data Center: How Nvidia, AMD, and Intel Compete for AI and HPC Dominance

The article examines how GPUs have evolved from gaming accelerators to essential data‑center processors for AI, HPC, and scientific workloads, and compares the latest server‑grade offerings from Nvidia, AMD, and Intel—including performance specs, memory technologies, interconnects, and software ecosystems—highlighting the fierce competition shaping the future of compute.

AIAMDHPC
0 likes · 12 min read
GPU Wars in the Data Center: How Nvidia, AMD, and Intel Compete for AI and HPC Dominance
ByteFE
ByteFE
May 18, 2022 · Frontend Development

Understanding WebGL: GPU Basics, Shaders, and Practical Code Examples

This article introduces WebGL fundamentals for frontend developers, explaining GPU versus CPU, GLSL shaders, and how JavaScript prepares data, followed by step‑by‑step code examples of fragment and vertex shaders, custom primitives, and using the gl‑renderer library to render graphics.

GraphicsJavaScriptShaders
0 likes · 11 min read
Understanding WebGL: GPU Basics, Shaders, and Practical Code Examples
Alibaba Terminal Technology
Alibaba Terminal Technology
May 17, 2022 · Frontend Development

Unlock 20‑30× GPU Speed: WebGPU in Three.js, Babylon.js, and TensorFlow.js

This article introduces WebGPU—a powerful yet still experimental web graphics API—showing how major frameworks like Three.js and Babylon.js adopt it for high‑performance 3D rendering, how TensorFlow.js leverages it for massive deep‑learning speedups, and provides hands‑on code examples from framework usage to raw WebGPU programming.

Babylon.jsGraphicsTensorFlow.js
0 likes · 17 min read
Unlock 20‑30× GPU Speed: WebGPU in Three.js, Babylon.js, and TensorFlow.js
Tencent Cloud Developer
Tencent Cloud Developer
May 12, 2022 · Backend Development

Practical Guide to PyTorch Distributed Training: DP, DDP, Groups, and IO Considerations

This guide explains PyTorch’s distributed training, contrasting single‑node DataParallel with multi‑node DistributedDataParallel, detailing essential parameters, group communication setup, proper use of DistributedSampler for data loading, handling IO bottlenecks, and avoiding common pitfalls such as memory imbalance, unsynchronized buffers, and unused‑parameter errors.

DDPDataParallelDistributed Training
0 likes · 15 min read
Practical Guide to PyTorch Distributed Training: DP, DDP, Groups, and IO Considerations
Architects' Tech Alliance
Architects' Tech Alliance
May 4, 2022 · Industry Insights

What the Next‑Gen Nvidia and AMD GPUs Could Mean for the 2022‑2023 Market

Based on recent leaks from 3DCenter.org and Twitter insiders Kopite7kimi and 暴龙兽55, the article forecasts Nvidia's Lovelace RTX 4000 series and AMD's RDNA 3 Navi 33/32 GPUs to launch between September 2022 and early 2023, analyzes their expected specifications, pricing dynamics, and potential market impact, and notes Intel's upcoming Arc cards as a wildcard.

AMDLovelaceNVIDIA
0 likes · 7 min read
What the Next‑Gen Nvidia and AMD GPUs Could Mean for the 2022‑2023 Market
Architects' Tech Alliance
Architects' Tech Alliance
Apr 19, 2022 · Artificial Intelligence

Overview of AI Chip Development, Architectures, and Market Trends in China (2022)

The article provides a comprehensive overview of AI chip technology, describing the dependence on mathematical models and semiconductor integration, classifying chips by architecture (GPU, FPGA, ASIC, SoC, brain‑like), deployment (cloud, edge, terminal), and outlining current challenges, market trends, and future research directions such as in‑memory and neuromorphic computing.

AI chipASICFPGA
0 likes · 11 min read
Overview of AI Chip Development, Architectures, and Market Trends in China (2022)
IT Services Circle
IT Services Circle
Apr 8, 2022 · Fundamentals

The Rise of Domestic GPUs in China: IP Licensing, Imagination Technologies, and Market Dynamics

Chinese domestic GPU development has accelerated rapidly, driven by fast‑track product launches, strategic IP licensing from firms like Imagination Technologies, and supportive policies, while industry players navigate challenges of patents, design complexity, and market competition to bring full‑function GPUs to market.

ChinaHardwareIP licensing
0 likes · 12 min read
The Rise of Domestic GPUs in China: IP Licensing, Imagination Technologies, and Market Dynamics
DataFunSummit
DataFunSummit
Apr 7, 2022 · Artificial Intelligence

Optimizing Distributed Machine Learning Training on Google Cloud Vertex AI: Fast Socket and Reduction Server

This article explains how Google Cloud Vertex AI improves large‑scale distributed machine learning training performance by addressing the memory‑wall challenge with Fast Socket network stack enhancements for NCCL and a Reduction Server that accelerates gradient aggregation, delivering higher throughput and lower TCO for AI workloads.

Cloud AIDistributed TrainingFast Socket
0 likes · 19 min read
Optimizing Distributed Machine Learning Training on Google Cloud Vertex AI: Fast Socket and Reduction Server
Python Programming Learning Circle
Python Programming Learning Circle
Mar 31, 2022 · Artificial Intelligence

Comprehensive PyTorch Code Snippets: Configuration, Tensor Operations, Model Definition, Training, and Best Practices

This article provides a thorough collection of commonly used PyTorch code snippets covering environment setup, reproducibility, GPU configuration, tensor manipulation, model building, data preprocessing, training and evaluation loops, custom loss functions, regularization techniques, learning‑rate scheduling, checkpointing, and practical tips for efficient deep‑learning development.

PythonTensor Operationsdeep learning
0 likes · 37 min read
Comprehensive PyTorch Code Snippets: Configuration, Tensor Operations, Model Definition, Training, and Best Practices
IT Services Circle
IT Services Circle
Mar 24, 2022 · Artificial Intelligence

NVIDIA Unveils H100 GPU with Hopper Architecture: Massive Performance Gains for AI

At the recent GTC event, NVIDIA introduced the H100 GPU built on the Hopper architecture using TSMC 4nm process, featuring 800 billion transistors, 16,896 CUDA cores, up to 700 W power, 3 TB/s memory bandwidth, and a specialized Transformer engine that accelerates large‑model training up to six times faster, alongside the Grace CPU Superchip and new AI supercomputing systems.

AIGrace CPUH100
0 likes · 11 min read
NVIDIA Unveils H100 GPU with Hopper Architecture: Massive Performance Gains for AI
JD Retail Technology
JD Retail Technology
Mar 24, 2022 · Mobile Development

Understanding Offscreen Rendering and Its Performance Impact in iOS

Offscreen rendering, a technique where the GPU or CPU renders content to a separate buffer outside the current screen framebuffer, can cause performance overhead due to buffer creation and context switches, and the article explains its principles, common trigger scenarios, and strategies to avoid it in iOS development.

CoreAnimationgpuiOS
0 likes · 11 min read
Understanding Offscreen Rendering and Its Performance Impact in iOS
IT Architects Alliance
IT Architects Alliance
Mar 10, 2022 · Industry Insights

What Drives the AI Chip Market? Types, Trends, and Future Outlook

The article provides a comprehensive overview of AI chips, explaining their broad and narrow definitions, core architectures such as GPU, FPGA, and ASIC, deployment scenarios from cloud to edge, training versus inference roles, current market dynamics, major vendors, and emerging application domains like autonomous driving and smart security.

AI chipsASICFPGA
0 likes · 9 min read
What Drives the AI Chip Market? Types, Trends, and Future Outlook
Architects' Tech Alliance
Architects' Tech Alliance
Mar 6, 2022 · Artificial Intelligence

Overview of AI Chip Technologies and Market Trends in China

The article provides a comprehensive overview of AI chips—including GPUs, FPGAs, and ASICs—their architectural distinctions, cloud and edge deployment models, market dynamics in China, and key application scenarios such as autonomous driving, smart security, and IoT devices.

AI chipsASICChina
0 likes · 7 min read
Overview of AI Chip Technologies and Market Trends in China
Meituan Technology Team
Meituan Technology Team
Mar 3, 2022 · Artificial Intelligence

GPU Optimization Practices for Meituan Delivery Search and Recommendation Model Inference

Meituan’s delivery search and recommendation service migrated from separate CPU‑only models to a unified multi‑task model running on a heterogeneous CPU‑GPU architecture, applying system‑level placement, All‑On‑GPU lookup, FP16 mixed precision, operator fusion, TensorRT and TVM compilation, which together delivered roughly a four‑fold increase in inference throughput while maintaining cost.

TVMTensorFlowgpu
0 likes · 24 min read
GPU Optimization Practices for Meituan Delivery Search and Recommendation Model Inference
Architects' Tech Alliance
Architects' Tech Alliance
Feb 16, 2022 · Fundamentals

Key Technology Trends Shaping High‑Performance Computing (HPC)

The article outlines major trends influencing high‑performance computing, including AI integration, GPU/TPU advancements, flexibility in processor architectures, HPC‑as‑a‑Service, hybrid cloud solutions, democratization, the emergence of exascale systems, and micro‑architectural improvements, while providing links to related reports and resources.

Artificial IntelligenceExascaleHPC
0 likes · 9 min read
Key Technology Trends Shaping High‑Performance Computing (HPC)
DataFunTalk
DataFunTalk
Jan 25, 2022 · Cloud Native

Model Deployment Challenges and a Seldon‑Based Cloud‑Native Solution

This article analyzes the complexities of deploying machine‑learning models in production, outlines the limitations of the existing ABox architecture, and details a comprehensive cloud‑native redesign using Seldon on Kubernetes—including custom HDFS initializers, GPU management, logging, and resource monitoring—to streamline operations and enable unified CPU/GPU model serving.

KubernetesMLOpsSeldon
0 likes · 12 min read
Model Deployment Challenges and a Seldon‑Based Cloud‑Native Solution
Youzan Coder
Youzan Coder
Jan 17, 2022 · Artificial Intelligence

Model Deployment Challenges and a Seldon‑Based Cloud‑Native Solution

The team replaced the cumbersome ABox deployment stack with Seldon‑based cloud‑native serving on Kubernetes, unifying TensorFlow and other framework models, adding GPU sharing, automated CRUD, per‑model ingress, monitoring, and log collection, achieving scalable, fault‑tolerant, zero‑downtime model deployment.

AI servingKubernetesSeldon
0 likes · 11 min read
Model Deployment Challenges and a Seldon‑Based Cloud‑Native Solution
Alimama Tech
Alimama Tech
Dec 22, 2021 · Artificial Intelligence

Performance Optimization of Advertising Deep Learning Systems: Algorithm, System, and Hardware Co‑Design

The paper presents a holistic algorithm‑system‑hardware co‑design for advertising deep‑learning inference, combining model pruning, approximate computing, kernel fusion, scheduling and PCIe transfer optimizations with GPU and NPU upgrades, achieving up to five‑fold speed‑up and significantly higher latency‑bounded QPS for large‑scale ad services.

Algorithmic OptimizationNPUPerformance Optimization
0 likes · 24 min read
Performance Optimization of Advertising Deep Learning Systems: Algorithm, System, and Hardware Co‑Design
58 Tech
58 Tech
Dec 21, 2021 · Artificial Intelligence

dl_inference: Open‑Source Deep Learning Inference Service with TensorRT and MKL Acceleration

dl_inference is an open‑source, production‑grade deep learning inference platform that supports TensorFlow, PyTorch and Caffe models, offering GPU and CPU deployment, TensorRT and MKL acceleration, multi‑node load balancing, and extensive Q&A on model conversion, hardware requirements, INT8 quantization, and performance gains.

CPUMKLTensorRT
0 likes · 8 min read
dl_inference: Open‑Source Deep Learning Inference Service with TensorRT and MKL Acceleration
Code DAO
Code DAO
Dec 17, 2021 · Artificial Intelligence

How to Scale XGBoost with Ray for Distributed Multi‑GPU Training

XGBoost‑Ray provides a fault‑tolerant, multi‑node, multi‑GPU backend for XGBoost that integrates seamlessly with Ray Tune, supports distributed data loading, and can be enabled with only three code changes, enabling scalable training and inference on large clusters.

Distributed TrainingRayRay Tune
0 likes · 8 min read
How to Scale XGBoost with Ray for Distributed Multi‑GPU Training
Architects' Tech Alliance
Architects' Tech Alliance
Dec 11, 2021 · Fundamentals

2021 China Integrated Circuit Market Research Report Overview

The 2021 China Integrated Circuit Market Research Report analyzes recent three‑year trends showing rising shares of MPU and logic chips, declining DRAM, stable analog and MCU, and details the market status, growth forecasts, and challenges for CPU, GPU, FPGA, ASIC, and storage technologies.

AI chipsCPUFPGA
0 likes · 11 min read
2021 China Integrated Circuit Market Research Report Overview
Architects' Tech Alliance
Architects' Tech Alliance
Nov 16, 2021 · Fundamentals

2021 China Integrated Circuit Market Research Report Overview

The 2021 China Integrated Circuit Market Research Report analyzes recent three‑year trends, showing rising shares for MPU and logic chips, declining DRAM, stable analog and MCU, while detailing the market positions, growth rates, and challenges of CPU, GPU, FPGA, ASIC, and flash storage technologies.

ASICCPUChina
0 likes · 11 min read
2021 China Integrated Circuit Market Research Report Overview
Architects' Tech Alliance
Architects' Tech Alliance
Nov 5, 2021 · Artificial Intelligence

GPU Architecture in the AI Era: From Specific‑Domain Designs to 3D/AI Fusion

The article analyzes how GPU architecture, originally designed for 3D graphics, is being reshaped by AI demands through specific‑domain designs, hardware/software interfaces, tensor acceleration, and 3D/AI convergence, ultimately arguing that GPUs will remain the central compute platform in the new golden age of computer architecture.

3D renderingArtificial IntelligenceNeural Rendering
0 likes · 14 min read
GPU Architecture in the AI Era: From Specific‑Domain Designs to 3D/AI Fusion
Architects' Tech Alliance
Architects' Tech Alliance
Oct 28, 2021 · Artificial Intelligence

GPU Technology Overview: Architecture, Market Landscape, and Key Application Directions

This article provides a comprehensive overview of GPU technology, covering its multi‑core architecture, market oligopoly among Intel, NVIDIA and AMD, classifications of integrated and independent GPUs, and the three major application trends of gaming performance, artificial intelligence/deep learning, and autonomous driving.

Artificial IntelligenceAutonomous DrivingHardware
0 likes · 14 min read
GPU Technology Overview: Architecture, Market Landscape, and Key Application Directions
Kuaishou Tech
Kuaishou Tech
Oct 25, 2021 · Fundamentals

Noise Techniques for Short Video Effects and Their Generation Algorithms

This article explores how various noise algorithms—including value, gradient, simplex, cellular, and FBM—are applied to short video visual effects, compares random number generators for GPU rendering, and provides GLSL code examples to illustrate implementation and performance trade‑offs.

Graphicsgpunoise
0 likes · 17 min read
Noise Techniques for Short Video Effects and Their Generation Algorithms
Kuaishou Large Model
Kuaishou Large Model
Oct 22, 2021 · Fundamentals

How Noise Powers Real‑Time Short‑Video Effects: Algorithms, Samples & GPU RNG Comparison

This article explains how various noise algorithms—value, gradient, simplex, cellular, and FBM—are applied to short‑video visual effects, showcases shader implementations and image examples, and compares GPU random‑number generators to help developers choose the right balance of performance and visual quality.

Random Number GenerationReal-time RenderingShader
0 likes · 17 min read
How Noise Powers Real‑Time Short‑Video Effects: Algorithms, Samples & GPU RNG Comparison
Xianyu Technology
Xianyu Technology
Oct 21, 2021 · Mobile Development

Flutter iOS GPU Background Crash Analysis and Solution

The article analyzes why Flutter crashes on iOS when accessing the GPU in the background, explains the official SyncSwitch fix for ImageDecoder, and details Xianyu’s additional patches for MultipleFrameCodec, EncodeImage, and Rasterizer::DrawToSurface that together, via PR #28383, fully resolve the GPU‑background crash.

CrashFlutterImageDecoder
0 likes · 11 min read
Flutter iOS GPU Background Crash Analysis and Solution
21CTO
21CTO
Oct 2, 2021 · Artificial Intelligence

How PyTorch Lightning Can Make Your Deep Learning Pipeline 10× Faster

This article explains six practical techniques—parallel data loading, distributed multi‑GPU training, mixed precision, early stopping, sharded training, and inference optimizations—using PyTorch Lightning to dramatically accelerate deep‑learning pipelines, turning days‑long experiments into minute‑scale runs.

Pipeline OptimizationPyTorch Lightningdeep learning
0 likes · 7 min read
How PyTorch Lightning Can Make Your Deep Learning Pipeline 10× Faster
Architects' Tech Alliance
Architects' Tech Alliance
Sep 23, 2021 · Fundamentals

Understanding High‑Performance Computing (HPC): Principles, Architecture, and Applications

The article explains high‑performance computing (HPC) concepts, including serial and parallel processing, supercomputer performance measured in FLOPS, real‑world scientific applications such as drug discovery and weather forecasting, and the hardware architectures that enable these massive computational capabilities.

FLOPSHPCcomputer architecture
0 likes · 7 min read
Understanding High‑Performance Computing (HPC): Principles, Architecture, and Applications
Meituan Technology Team
Meituan Technology Team
Sep 9, 2021 · Artificial Intelligence

GPU Optimization Practices for CTR Models at Meituan

Meituan accelerates CTR model inference by fusing operators with TVM, optimizing CPU‑GPU data transfers, manually tuning high‑frequency subgraphs, and dynamically offloading workloads, achieving up to ten‑fold throughput gains on Tesla T4 GPUs while keeping latency stable and only modestly increasing beyond 128 QPS, though compilation remains slow and large‑model support needs improvement.

CTRTVMTensorFlow
0 likes · 16 min read
GPU Optimization Practices for CTR Models at Meituan
Liangxu Linux
Liangxu Linux
Aug 17, 2021 · Cloud Native

How to Enable GPU Acceleration in Docker on Linux

This guide walks you through installing NVIDIA drivers, CUDA, and nvidia-docker2 on a Linux host, configuring Docker to access the GPU, and verifying the setup with commands and sample TensorFlow/PyTorch code, enabling deep‑learning workloads inside containers.

CUDADockerNVIDIA
0 likes · 7 min read
How to Enable GPU Acceleration in Docker on Linux
DataFunSummit
DataFunSummit
Aug 16, 2021 · Artificial Intelligence

Scaling Deep Learning Models: From Depth to Width and Parallelism Strategies

The article reviews how deep learning models have grown deeper and wider, discusses the memory and bandwidth limits of single GPUs, and explains pipeline and sharding techniques—including GPU clusters and TPU pods—to efficiently train large‑scale models in industrial settings.

Mixture of ExpertsTPUgpu
0 likes · 6 min read
Scaling Deep Learning Models: From Depth to Width and Parallelism Strategies
Architects' Tech Alliance
Architects' Tech Alliance
Jul 16, 2021 · Artificial Intelligence

AI Chip Landscape: GPUs, FPGAs, and ASICs for Deep Learning

The article explains how artificial intelligence relies on algorithms, compute and data, compares engineering and simulation methods, and details the roles, architectures, performance and energy characteristics of GPUs, FPGAs, and ASICs as the primary hardware accelerators for modern deep‑learning applications.

ASICArtificial IntelligenceFPGA
0 likes · 14 min read
AI Chip Landscape: GPUs, FPGAs, and ASICs for Deep Learning
Architects' Tech Alliance
Architects' Tech Alliance
Jun 29, 2021 · Artificial Intelligence

Evolution and Future Trends of Automotive Chips for Autonomous Driving

The article reviews the historical shift from CPU‑based ECUs to GPU‑centric and ASIC‑centric automotive processors, analyzes current GPU dominance, examines key industry players, and discusses why ASICs are expected to become the primary solution for future autonomous‑driving chips.

AI hardwareASICautomotive chips
0 likes · 16 min read
Evolution and Future Trends of Automotive Chips for Autonomous Driving