BestHub
Sign in
Tagged articles

Cache Optimization

53 articles · Page 1 of 1
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Aug 11, 2026 · Artificial Intelligence

How Pi’s Harness Achieves a 99.93% Cache Hit Rate for DeepSeek and Cuts Cost Up to 7×

The open‑source Pi harness for DeepSeek delivers a 99.93% cache hit rate, reducing token‑processing costs to $0.028 per successful task—about seven times cheaper than Claude Code—while supporting extensible file‑operation tools and demonstrating dramatic cost differences across competing agent harnesses.

Cache OptimizationDeepSeekLLM Cost
0 likes · 9 min read
How Pi’s Harness Achieves a 99.93% Cache Hit Rate for DeepSeek and Cuts Cost Up to 7×
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Jul 29, 2026 · Artificial Intelligence

Why Cache Hit Rate Beats Model IQ in AI Programming Costs

The article shows that in AI‑assisted coding the real cost driver is cache hit rate, not model intelligence, using a lawyer‑memory analogy, hierarchical caching details, three SGLang PR fixes, token‑usage statistics, benchmark scores, and four concrete task‑level observations that together explain how Agnes 2.5 Pro Alpha reduces latency and expense.

AI programmingAgnesAICache Optimization
0 likes · 22 min read
Why Cache Hit Rate Beats Model IQ in AI Programming Costs
James' Growth Diary
James' Growth Diary
Jun 18, 2026 · Artificial Intelligence

Externalizing Agent Decisions to Files: How a Three‑Layer Prompt Architecture Drives Behavior

The article examines Hermes' design that moves all agent decision rules into editable text files, explains the three‑layer stable‑context‑volatile architecture, compares it with other frameworks, and shows how this approach improves transparency, controllability, and cache efficiency for AI agents.

AI safetyAgent ArchitectureCache Optimization
0 likes · 11 min read
Externalizing Agent Decisions to Files: How a Three‑Layer Prompt Architecture Drives Behavior
IT Services Circle
IT Services Circle
Jun 10, 2026 · Fundamentals

Why a Mathematically Free Matrix Transpose Is 10× Slower on CPUs

A naive 1024×1024 matrix transpose can be ten times slower than an optimized version because the CPU sees memory as a linear address space, and row‑major layout combined with cache‑line granularity makes column‑wise accesses incur massive cache misses, which can be eliminated with blocking, prefetching and SIMD techniques.

CPU architectureCache OptimizationSIMD
0 likes · 19 min read
Why a Mathematically Free Matrix Transpose Is 10× Slower on CPUs
James' Growth Diary
James' Growth Diary
May 21, 2026 · Artificial Intelligence

Why Hermes Agent Stands Out: From One‑Shot Tool to Long‑Term Partner

The article explains how Hermes Agent redesigns AI agents to grow like a partner—adding persistent multi‑layer memory, autonomous skill learning, model‑agnostic architecture, multi‑platform unification and safe autonomous behavior—addressing the shortcomings of typical one‑off AI tools.

AI Agent ArchitectureCache OptimizationHermes Agent
0 likes · 12 min read
Why Hermes Agent Stands Out: From One‑Shot Tool to Long‑Term Partner
JavaGuide
JavaGuide
May 9, 2026 · Artificial Intelligence

DeepSeek V4 vs GLM‑5.1: Which AI Coding Model Offers the Best Cost‑Performance?

The article compares DeepSeek V4 and GLM‑5.1 AI coding models by analyzing their pricing structures, cache‑hit mechanisms, real‑world billing data, and suitability for different coding workloads, ultimately offering guidance on when each model provides the most cost‑effective solution.

AI codingCache OptimizationDeepSeek
0 likes · 12 min read
DeepSeek V4 vs GLM‑5.1: Which AI Coding Model Offers the Best Cost‑Performance?
SuanNi
SuanNi
May 4, 2026 · Artificial Intelligence

Why Prompt Caching Is Everything for Claude Code

The article explains how Claude Code achieves extreme speed and low cost by building its architecture around a static prompt prefix, detailing the mechanics of prompt caching, safe model and tool switching, plan‑mode tooling, deferred loading, and cache‑safe context compression.

AI agentsAnthropicCache Optimization
0 likes · 10 min read
Why Prompt Caching Is Everything for Claude Code
AI Tech Publishing
AI Tech Publishing
May 1, 2026 · Artificial Intelligence

5 Counterintuitive Design Principles for Prompt Caching in Claude Code

The article details five counterintuitive design principles for Claude Code's prompt caching—optimizing prompt layout, using message‑based updates, never switching models or tools mid‑conversation, safely compressing context, and monitoring cache health—backed by concrete examples and up to 90% cost savings.

AI EngineeringCache OptimizationClaude Code
0 likes · 10 min read
5 Counterintuitive Design Principles for Prompt Caching in Claude Code
AI Architecture Hub
AI Architecture Hub
Apr 23, 2026 · Artificial Intelligence

Why Prompt Caching Is Critical: Lessons from Building Claude Code

Prompt caching, a prefix‑matching technique that reuses prior LLM interactions, proved essential for Claude Code’s low latency and cost, and the article details counter‑intuitive practices such as arranging static prompts first, updating info via messages, avoiding mid‑session model or tool changes, and ensuring cache‑safe context forks.

AI EngineeringCache OptimizationClaude Code
0 likes · 10 min read
Why Prompt Caching Is Critical: Lessons from Building Claude Code
Tencent Cloud Developer
Tencent Cloud Developer
Mar 4, 2026 · Artificial Intelligence

How OpenClaw Uses a Multi‑Layer Defense System to Prevent LLM Context Overflow

The article provides a detailed technical walkthrough of OpenClaw's three‑stage context‑management framework—including pre‑emptive pruning, LLM‑driven compaction, and overflow‑recovery truncation—showing how each layer protects long‑running AI agent sessions from exceeding token windows while preserving essential information.

Cache OptimizationContext ManagementLLM
0 likes · 27 min read
How OpenClaw Uses a Multi‑Layer Defense System to Prevent LLM Context Overflow
Alibaba Cloud Developer
Alibaba Cloud Developer
Jan 4, 2026 · Databases

Accelerating AliSQL Vector Search with Nodes Cache and SIMD

AliSQL 8.0 introduces a shared Nodes Cache and per‑transaction cache to speed up vector queries, implements RC‑level transaction isolation for read‑only and read‑write operations, and leverages SIMD‑based pre‑computation to dramatically improve high‑dimensional vector distance calculations and concurrency performance.

AliSQLCache OptimizationSIMD
0 likes · 9 min read
Accelerating AliSQL Vector Search with Nodes Cache and SIMD
Deepin Linux
Deepin Linux
Dec 2, 2025 · Fundamentals

Why CPU Cache Misses Slow Down Your Linux System—and How to Fix Them

CPU caches bridge the speed gap between processors and memory, but cache misses can dramatically degrade performance, especially under high concurrency or big‑data workloads; this article explains cache architecture, common miss causes, diagnostic tools like perf and cachestat, and practical optimization techniques for Linux systems.

CPU cacheCache OptimizationLinux performance
0 likes · 44 min read
Why CPU Cache Misses Slow Down Your Linux System—and How to Fix Them
Alipay Experience Technology
Alipay Experience Technology
Aug 22, 2025 · Fundamentals

Designing Adaptive Time‑Window Formulas: From Theory to Real‑World Cache Optimization

This article explores how to replace fixed‑parameter cache‑expiration settings with mathematically derived, adaptive time‑window formulas that start slow, accelerate, and respect upper bounds, using linear, exponential, and sigmoid models refined through large‑model assistance.

Cache Optimizationalgorithm designmathematical modeling
0 likes · 10 min read
Designing Adaptive Time‑Window Formulas: From Theory to Real‑World Cache Optimization
Bilibili Tech
Bilibili Tech
Jul 4, 2025 · Operations

Solving CPU Performance Layering in Heterogeneous Data Centers: A Practical Guide

This article explains why heterogeneous servers cause CPU performance layering, describes how to detect the issue using metrics such as NUMA hit/miss rates, cache miss ratios and frequency states, and provides step‑by‑step remediation techniques—including NUMA binding, cache isolation, recompilation and frequency locking—to improve resource pooling efficiency in modern data centers.

CPU performanceCache OptimizationData Center
0 likes · 24 min read
Solving CPU Performance Layering in Heterogeneous Data Centers: A Practical Guide
JD Tech Talk
JD Tech Talk
Jul 1, 2025 · Fundamentals

How False Sharing Slows Down Multithreaded Java Apps—and How to Fix It

This article explains the hidden performance killer of cache false sharing in multicore Java applications, demonstrates its impact with benchmark code, and shows how padding, the @Contended annotation, and Caffeine's internal structures can eliminate the issue for faster execution.

Cache OptimizationCaffeineContended
0 likes · 10 min read
How False Sharing Slows Down Multithreaded Java Apps—and How to Fix It
JD Cloud Developers
JD Cloud Developers
Jul 1, 2025 · Fundamentals

How False Sharing Slows Your Java Apps and How to Eliminate It

This article explains the cache architecture behind false sharing, demonstrates its dramatic performance impact with benchmark code, and shows how Java's @Contended annotation and Caffeine's memory‑padding techniques can effectively eliminate the issue for high‑concurrency applications.

Cache Optimizationfalse sharingperformance-tuning
0 likes · 10 min read
How False Sharing Slows Your Java Apps and How to Eliminate It
Linux Kernel Journey
Linux Kernel Journey
Feb 5, 2025 · Fundamentals

Boost Code Performance by Leveraging CPU Cache Principles

This article explains how CPU caches bridge the speed gap between the processor and main memory, describes cache hierarchy, locality principles, write policies, coherence protocols, and provides concrete C code examples and practical tips such as data alignment and loop restructuring to improve cache hit rates and overall program speed.

CPU cacheCache OptimizationMESI Protocol
0 likes · 30 min read
Boost Code Performance by Leveraging CPU Cache Principles
JD Tech Talk
JD Tech Talk
Jan 22, 2025 · Operations

Preface

This article addresses a high-concurrency inventory problem in a second-hand market's second-hand market system, focusing on solving the system's inventory deduction issue during flash sales using cache and asynchronous processing to achieve horizontal scalability.

Cache OptimizationTransaction Handlinghigh concurrency
0 likes · 10 min read
Preface
iQIYI Technical Product Team
iQIYI Technical Product Team
Nov 21, 2024 · Big Data

Alluxio Integration and Optimization for Multi‑AZ Big Data Analytics at iQIYI

iQIYI integrates Alluxio with its QBFS multi‑AZ unified scheduling system, automatically caching hot tables, applying table‑level policies, page‑level storage and AZ‑aware worker selection, which together cut cross‑zone traffic, halve query latency, achieve up to 20× I/O speedup and a three‑fold overall performance boost.

AlluxioCache OptimizationData Lake
0 likes · 23 min read
Alluxio Integration and Optimization for Multi‑AZ Big Data Analytics at iQIYI
StarRocks
StarRocks
Jul 2, 2024 · Big Data

What’s New in StarRocks 3.3? Deep Dive into Lakehouse‑Optimized Performance and Features

StarRocks 3.3 introduces a comprehensive set of enhancements—including maturity levels, ARM‑optimized performance, advanced caching, materialized‑view rewrites, storage optimizations, and expanded lakehouse ecosystem support—that together boost stability, query speed, and usability for large‑scale analytics workloads.

Big DataCache OptimizationLakehouse
0 likes · 15 min read
What’s New in StarRocks 3.3? Deep Dive into Lakehouse‑Optimized Performance and Features
IT Niuke
IT Niuke
Jan 21, 2024 · Databases

Implementing Pagination and Multi‑Condition Fuzzy Search in Redis

The article explains how to use Redis Sorted Sets for efficient pagination, employ Hashes with HSCAN for multi‑condition fuzzy matching, combine both techniques into a unified solution, and apply expiration‑based optimizations to keep the cache lightweight and responsive.

Cache OptimizationFuzzy SearchHash
0 likes · 10 min read
Implementing Pagination and Multi‑Condition Fuzzy Search in Redis
Architect's Guide
Architect's Guide
Nov 24, 2023 · Databases

Implementing Conditional Query and Pagination with Redis

This article explains how to use Redis' Sorted Set and Hash structures to achieve efficient pagination, multi‑condition fuzzy queries, and their combination, while also discussing performance optimizations such as expiration handling and data synchronization strategies.

Cache OptimizationFuzzy QueryHash
0 likes · 10 min read
Implementing Conditional Query and Pagination with Redis
vivo Internet Technology
vivo Internet Technology
Oct 25, 2023 · Backend Development

Optimizing Dubbo Routing and Load Balancing at Scale: Vivo's Practice

Vivo tackled high CPU overhead in large‑scale Dubbo deployments by disabling unused routers, caching routing results with BitMap intersections and epoch validation, optimizing weight calculations, and adding a grouping router, which together delivered over 100 % TPS gains for 20 k+ providers and cut CPU usage by roughly 27 %.

Backend ArchitectureCache OptimizationDubbo
0 likes · 18 min read
Optimizing Dubbo Routing and Load Balancing at Scale: Vivo's Practice
Open Source Linux
Open Source Linux
Aug 17, 2023 · Fundamentals

Why CPU Cache Matters: Unlock Faster Code Execution

This article explains the purpose of CPU caches, their hierarchical structure and internal designs—including direct‑mapped, set‑associative, and fully‑associative caches—and demonstrates how understanding cache behavior can dramatically improve program performance, illustrated with C++ traversal benchmarks.

CPU cacheCache Optimizationcache hierarchy
0 likes · 12 min read
Why CPU Cache Matters: Unlock Faster Code Execution
Java Architect Essentials
Java Architect Essentials
Jun 13, 2023 · Fundamentals

How Bloom, Counting Bloom, and Cuckoo Filters Cut Database I/O

To reduce costly database I/O, the article explains how Bloom filters, Counting Bloom filters, and Cuckoo filters work, detailing their bitmap/hash mechanisms, false‑positive behavior, deletion limitations, and practical enhancements such as multi‑hash functions and bucket‑level fingerprints.

Bloom filterCache OptimizationCounting Bloom
0 likes · 13 min read
How Bloom, Counting Bloom, and Cuckoo Filters Cut Database I/O
Laravel Tech Community
Laravel Tech Community
Jun 6, 2023 · Fundamentals

Understanding Bloom Filters, Counting Bloom Filters, and Cuckoo Filters

This article explains how Bloom filters, their counting variant, and Cuckoo filters work to reduce unnecessary database I/O by using bitmap or fingerprint techniques, discusses their false‑positive and deletion limitations, and presents practical optimizations for high‑performance hash‑based filtering.

Bloom filterCache OptimizationCounting Bloom Filter
0 likes · 11 min read
Understanding Bloom Filters, Counting Bloom Filters, and Cuckoo Filters
Bilibili Tech
Bilibili Tech
May 19, 2023 · Backend Development

Local Cache Optimization for Outbox Redis in a High‑Traffic Feed Stream Service

To protect the outbox Redis cluster from extreme read amplification during hot events, the service adds a resident local cache for hot creators’ latest posts, using a threshold‑based list, change‑broadcast updates, and checksum verification, which achieved over 55% cache hits and cut peak Redis load by roughly 44% and CPU usage by 37%.

Cache OptimizationPerformance ScalingRedis
0 likes · 10 min read
Local Cache Optimization for Outbox Redis in a High‑Traffic Feed Stream Service
dbaplus Community
dbaplus Community
Mar 22, 2023 · Databases

Scaling an Airline Ticket Order Database: From Monolith to 64‑Shard Sharding

The article details how a rapidly growing airline ticket order system was re‑architected by identifying performance bottlenecks, applying vertical and horizontal sharding, optimizing cache layers, implementing dual‑write mechanisms, and planning a phased migration to achieve ten‑fold QPS growth while reducing resource usage and operational risk.

Cache OptimizationMySQLdatabase sharding
0 likes · 38 min read
Scaling an Airline Ticket Order Database: From Monolith to 64‑Shard Sharding
Baidu Geek Talk
Baidu Geek Talk
Dec 14, 2022 · Databases

How Baidu’s HybridIndexTable Redefined Inverted Index Performance

This article examines Baidu's Limitless ad‑funnel optimization, detailing how a cache‑friendly HybridIndexTable and adaptive memory containers dramatically improve inverted‑list scan speed, reduce memory overhead, and enable lock‑free updates for high‑throughput retrieval systems.

Cache OptimizationHybridIndexTableLearned Index
0 likes · 17 min read
How Baidu’s HybridIndexTable Redefined Inverted Index Performance
Top Architect
Top Architect
Jan 20, 2022 · Fundamentals

Understanding Bloom Filter, Counting Bloom Filter, and Cuckoo Filter: Principles, Issues, and Optimizations

This article explains the concepts, advantages, and limitations of Bloom filters, Counting Bloom filters, and Cuckoo filters, illustrating how they reduce unnecessary I/O in backend systems and offering practical improvements such as multi‑hash functions and bucket designs to enhance space and time efficiency.

Cache OptimizationCounting Bloom FilterCuckoo Filter
0 likes · 13 min read
Understanding Bloom Filter, Counting Bloom Filter, and Cuckoo Filter: Principles, Issues, and Optimizations
Top Architect
Top Architect
Dec 30, 2021 · Fundamentals

Understanding Bloom Filter, Counting Bloom Filter, and Cuckoo Filter: Principles, Issues, and Optimizations

This article explains the motivation behind using probabilistic filters to reduce I/O, describes how Bloom filters, Counting Bloom filters, and Cuckoo filters work, analyzes their false‑positive and deletion problems, and presents practical optimizations such as multiple hash functions and multi‑slot buckets.

Bloom filterCache OptimizationCounting Bloom Filter
0 likes · 12 min read
Understanding Bloom Filter, Counting Bloom Filter, and Cuckoo Filter: Principles, Issues, and Optimizations
Top Architect
Top Architect
Oct 29, 2021 · Fundamentals

Understanding Bloom Filters, Counting Bloom Filters, and Cuckoo Filters

The article explains how Bloom filters, Counting Bloom filters, and Cuckoo filters work, their hash‑based bitmap mechanisms, advantages and limitations such as false positives and deletion issues, and presents practical improvements and hash functions for efficient cache and database query optimization.

Bloom filterCache OptimizationCuckoo Filter
0 likes · 12 min read
Understanding Bloom Filters, Counting Bloom Filters, and Cuckoo Filters
IT Architects Alliance
IT Architects Alliance
Oct 28, 2021 · Fundamentals

Understanding Bloom Filters, Counting Bloom Filters, and Cuckoo Filters

The article explains the principles, advantages, and limitations of Bloom filters, introduces Counting Bloom filters as an enhanced version, and then details Cuckoo filters and Cuckoo hashing, including their algorithms, performance trade‑offs, and practical improvements for reducing unnecessary I/O operations.

Bloom filterCache OptimizationCounting Bloom Filter
0 likes · 11 min read
Understanding Bloom Filters, Counting Bloom Filters, and Cuckoo Filters
Dada Group Technology
Dada Group Technology
Oct 15, 2021 · Backend Development

Redis Cache Optimization and Architecture Evolution in JD Daojia Coupon System

This article details the JD Daojia coupon system's high‑traffic architecture, describing its multi‑layer design, Redis cache challenges such as large‑key and hot‑key issues, and practical optimization techniques including key redesign, expiration strategies, and active‑expire algorithms to improve performance and scalability.

Cache OptimizationRediscoupon system
0 likes · 17 min read
Redis Cache Optimization and Architecture Evolution in JD Daojia Coupon System
Tencent Cloud Developer
Tencent Cloud Developer
Jul 21, 2021 · Big Data

Bloom Filter: Introduction, Theory, Construction, Query, and Applications

The article explains Bloom filters—a probabilistic, space‑efficient data structure using multiple hash functions on a bit array to answer set‑membership queries with controllable false‑positive rates, detailing their construction, query process, optimal parameters, and common uses such as URL deduplication, cache protection, and spam filtering.

Big DataBloom filterCache Optimization
0 likes · 8 min read
Bloom Filter: Introduction, Theory, Construction, Query, and Applications
Architects' Tech Alliance
Architects' Tech Alliance
Apr 11, 2021 · Industry Insights

How to Supercharge Ceph on Huawei Kunpeng ARM: Deep Performance Tuning Guide

This article examines Ceph’s architecture, identifies performance bottlenecks on Huawei’s Kunpeng ARM platform, and presents practical tuning methods—including NUMA placement, cache tagging, vector acceleration, thread scaling, and monitoring tools—to improve storage efficiency, reduce latency, and lower power consumption.

ARMCache OptimizationCeph
0 likes · 17 min read
How to Supercharge Ceph on Huawei Kunpeng ARM: Deep Performance Tuning Guide
JavaEdge
JavaEdge
Nov 30, 2020 · Backend Development

How Kafka’s Index Uses Binary Search and Cache‑Friendly Optimizations

This article explains Kafka's index architecture, the AbstractIndex class hierarchy, how entry sizes are chosen, the use of memory‑mapped files, the binary‑search algorithm for locating index entries, and a cache‑friendly improvement that reduces page faults and I/O latency.

Cache OptimizationIndexKafka
0 likes · 13 min read
How Kafka’s Index Uses Binary Search and Cache‑Friendly Optimizations
Tencent Cloud Developer
Tencent Cloud Developer
Jan 10, 2020 · Cloud Computing

Tencent Classroom Cloud VOD HLS Playback Architecture and Optimization

The article outlines Tencent Classroom’s cloud VOD solution, detailing HLS streaming fundamentals, a Mongoose‑based local HTTP proxy with LFU caching and pre‑loading, performance optimizations for latency, buffering, security, and playback reliability, and common transcoding pitfalls with practical fixes, highlighting cloud migration benefits.

Cache OptimizationStreamingTencent Cloud
0 likes · 13 min read
Tencent Classroom Cloud VOD HLS Playback Architecture and Optimization
Tencent Database Technology
Tencent Database Technology
Nov 7, 2019 · Databases

MonetDB: History, Storage Model, Execution Model, Architecture, and Key Technologies

This article provides a comprehensive overview of MonetDB, covering its origins at CWI, column‑oriented storage with BATs, memory‑mapped and vectorized execution, three‑layer system architecture, cache‑aware optimizations such as vector operations and radix‑partitioned hash joins, as well as its limitations and reference sources.

Cache OptimizationColumnar DatabaseMonetDB
0 likes · 10 min read
MonetDB: History, Storage Model, Execution Model, Architecture, and Key Technologies
dbaplus Community
dbaplus Community
Oct 27, 2019 · Databases

How Weibo Scales Redis: Architecture, Optimizations, and Future Plans

This article details how Weibo leverages Redis across billions of requests, describing its massive scale, the challenges of trillion‑level reads/writes, the technical choices and customizations made—including LongSet, HA solutions, multi‑level caching, RocksDB integration—and outlines ongoing capacity and future development strategies.

Cache OptimizationDatabase ScalingHigh Availability
0 likes · 18 min read
How Weibo Scales Redis: Architecture, Optimizations, and Future Plans
Meituan Technology Team
Meituan Technology Team
Dec 20, 2018 · Backend Development

Design and Performance Optimization of LruCache in Meituan DSP System

Meituan’s DSP system boosted high‑QPS ad serving performance by layering an LRU cache in front of Redis, then adding time‑based eviction, sharding the cache into HashLruCache instances to cut lock contention, and employing a zero‑copy, reference‑counted design, ultimately cutting average latency to about 20 % of the original and similarly reducing 99.9th‑percentile delays.

Cache OptimizationHashLruCacheHigh QPS
0 likes · 15 min read
Design and Performance Optimization of LruCache in Meituan DSP System
iQIYI Technical Product Team
iQIYI Technical Product Team
Jan 12, 2018 · Backend Development

Couchbase Caching Optimization and Case Studies in iQIYI's Bubble Social Backend

The article details iQIYI’s Bubble social service cache architecture, comparing Couchbase and Redis, explaining vBucket design and management UI, and presenting three real‑world optimizations—like‑system key redesign, voting‑system aggregation, and SDK upgrade—along with migration, synchronization, and operational best‑practice recommendations.

Cache OptimizationCouchbaseRedis
0 likes · 16 min read
Couchbase Caching Optimization and Case Studies in iQIYI's Bubble Social Backend
Aotu Lab
Aotu Lab
Jun 30, 2017 · Frontend Development

Understanding Pagination: Traditional vs. Infinite Scrolling and How to Implement Them

This article explains the differences between traditional page‑number pagination and infinite‑scroll (streaming) pagination, compares their characteristics, and provides detailed front‑end and back‑end implementation methods along with common pitfalls and optimization techniques such as caching, cursor‑based paging, and client‑side deduplication.

Cache OptimizationCursor Paginationback-end development
0 likes · 12 min read
Understanding Pagination: Traditional vs. Infinite Scrolling and How to Implement Them
21CTO
21CTO
Oct 3, 2015 · Fundamentals

Why Cache Mechanisms Follow Fractal Geometry: A Deep Dive into Space‑Time Trade‑offs

This article explores how various caching techniques—from DNS and CDN to browser and hardware caches—exhibit self‑similar fractal patterns, illustrating the universal space‑for‑time trade‑off that improves system efficiency across front‑end, back‑end, and real‑world scenarios.

Cache OptimizationFrontendWeb Performance
0 likes · 15 min read
Why Cache Mechanisms Follow Fractal Geometry: A Deep Dive into Space‑Time Trade‑offs
Baidu Tech Salon
Baidu Tech Salon
May 28, 2014 · Game Development

C++ Performance Optimization Techniques for Ray Tracing

The article outlines 27 C++ performance optimization techniques for ray tracing, emphasizing profiling hot paths, minimizing branches and memory accesses, using inline and reference passing, aligning data, loop unrolling, avoiding unnecessary temporaries, and simplifying math to exploit cache locality and modern CPU parallelism.

Amdahl's lawC++ optimizationCache Optimization
0 likes · 12 min read
C++ Performance Optimization Techniques for Ray Tracing