'concurrent' 검색 결과

Swift 6.2 마이그레이션과 동시성 설계를 돕습니다. MainActor로 상태를 보호하고 데이터 경쟁 컴파일 오류, 프로토콜 준수, 고부하 계산의 명시적 백그라운드 실행을 다룹니다.

• 기존 앱을 Swift 6.2로 마이그레이션
• 데이터 경쟁 컴파일 오류 해결
• 고부하 계산을 백그라운드로 분리

Build concurrent Go applications with goroutines, lightweight execution units, and channels for communication. Apply patterns for worker pools, cancellation, synchronization, and orderly shutdown, and investigate race conditions when concurrent operations access shared data.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Implement a worker pool for concurrent jobs
• Connect processing stages with channels
• Manage cancellation and orderly shutdown

Build Python applications that handle other work while waiting for network or database operations. Use asyncio and async/await to run tasks concurrently, manage errors and timeouts, and handle cancellation with appropriate cleanup.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building web APIs that handle many simultaneous requests
• Fetching data from multiple sources concurrently
• Implementing WebSocket servers and chat systems

Build Go services and command-line tools with clear interfaces, explicit error handling, and concurrent tasks using goroutines and channels. Use pprof to investigate performance, then check behavior with benchmarks, structured test cases, fuzzing, and race detection.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Implementing concurrent tasks with cancellation and error handling
• Building gRPC or REST services and command-line tools
• Investigating Go performance with pprof and benchmarks

운영 데이터베이스의 열, 인덱스와 데이터 변경을 설계합니다. 대규모 테이블의 분할 갱신, 단계적 구조 전환과 복구 계획을 포함해 마이그레이션 절차를 정리합니다.

• 대규모 테이블에 열과 인덱스 추가
• 중단을 피하는 단계적 열 이름 변경
• 기존 데이터의 분할 보완

Measure performance in the agentic-flow worker system, including trigger detection, agent selection, caching, and concurrent operations. Run a full suite or individual benchmarks to compare response times and resource usage against configured targets.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking overall worker system performance
• Measuring trigger detection and agent selection speed
• Examining cache behavior and memory usage

Reproduce timing and ordering bugs in a CTF sandbox using controlled concurrent requests. Compare normal and racing runs, trace reads and writes, and preserve a minimal sequence that demonstrates duplicate actions or inconsistent state.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reproduce bugs triggered by simultaneous requests
• Investigate duplicate actions and ineffective duplicate prevention
• Trace stale reads and gaps in locking

Build and debug asynchronous Rust applications with Tokio, a runtime for scheduling work while operations wait. Apply patterns for task management, channels, error handling, cancellation, and concurrency limits when developing network services and other concurrent systems.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build asynchronous network services
• Manage tasks and channel communication
• Design error handling and cancellation

Model distributed systems and concurrent algorithms in TLA+ or PlusCal, then check possible states with TLC. Use the results to investigate deadlocks, broken rules, and differences between specifications and implementation code.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Model a distributed protocol before implementation
• Create a specification from existing concurrent code
• Investigate deadlocks and race conditions

Fix PostgreSQL deadlock errors caused by concurrent schema initialization in worker processes. Use when: (1) psycopg2.errors.DeadlockDetected during CREATE INDEX/TABLE IF NOT EXISTS, (2) Multiple Cloud Run jobs, Kubernetes pods, or worker processes start simultaneously, (3) Error shows "Process X waits for RowExclusiveLock... blocked by process Y", (4) init_schema() or migration code runs at worker startup. The key insight: "IF NOT EXISTS" is NOT truly concurrent-safe - PostgreSQL still acquires locks that can deadlock.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Organize a task into parallel work streams with clear dependencies, separate places for changes, and explicit checks. Batch independent reads and tests, coordinate concurrent work, and report completed or blocked tasks with verification results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Batching independent file reads and searches
• Splitting implementation across multiple agents
• Separating changes with Git worktrees

Go 언어의 관례에 따라 코드 작성, 검토, 리팩터링을 돕습니다. 오류 처리, 동시성, 패키지 구성을 정리해 읽기 쉽고 유지보수하기 좋은 구현을 지향합니다.

• Go 관례에 맞춰 코드 검토
• 기존 코드의 오류 처리 개선
• 취소할 수 있는 동시 작업 설계

Implement distributed data synchronization with CRDTs, data structures designed to merge concurrent updates. Covers counters, sets, shared values, and sequences, with incremental updates and tracking of dependencies between operations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Implementing shared counters across multiple nodes
• Merging concurrent additions and removals in shared sets
• Sending only changes during data synchronization

Take implementation work through small, independently mergeable pull requests. Use a separate working directory for each PR, record manual QA evidence, write English review descriptions, resolve CI and review findings, then merge and clean up.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Deliver implementation work through pull requests
• Split a large task into small, independently mergeable PRs
• Build independent PRs concurrently

Design agents that respond to incoming emails, external notifications, and timers. Plan how they handle interruptions, prioritize new requests, track concurrent tasks, and deliver results while longer operations continue in the background.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Connecting agents to incoming emails and external notifications
• Scheduling reports and recurring checks
• Handling interruptions and changes during long tasks

Build Python applications that keep other tasks moving while waiting for network, database, or file operations. Guides the choice of asyncio patterns, with timeouts, cancellation, error handling, and testing for asynchronous code.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build an asynchronous web API
• Fetch multiple web pages concurrently
• Develop a WebSocket server or chat system

Design storage for event sourcing, an approach that records changes as events. Compare database options and plan event ordering, duplicate handling, concurrent writes, and scaling to build a consistent event persistence layer.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Compare event storage technologies
• Design event schemas and streams
• Handle concurrent and duplicate writes

Review C# asynchronous code and get suggestions for method names, return types, exception handling, concurrent tasks, and cancellation. Identify blocking calls and missing awaits, and choose patterns for long operations or sequences processed asynchronously.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing async/await usage
• Finding blocking calls and missing awaits
• Planning concurrent tasks and cancellation

Analyze LLM serving traces to identify GPU time usage, opportunities to run operations concurrently, and known patterns for combining operations. Produce three consistent tables from saved traces or live captures on supported servers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Identify GPU operations that dominate inference time
• Compare input processing and token generation
• Trace GPU operations back to Python code

Build Python applications that keep other tasks moving while waiting for network, file, or database operations. The skill guides asyncio patterns, task cancellation, timeouts, workload limits, and testing for asynchronous APIs, scrapers, and background processing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building asynchronous web APIs
• Sending concurrent requests in web scrapers
• Designing background tasks and queues

Write and review asynchronous C++ networking code using Boost.Asio or standalone Asio. The skill selects an implementation style for the installed library and C++ version, then checks memory lifetimes, concurrent writes, error handling, and build settings.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Implementing asynchronous TCP or UDP servers and clients
• Reviewing buffer lifetimes and concurrent socket writes
• Adapting networking code to older Boost and C++ versions

Helps choose and tune Cloud Storage FUSE mounts, which expose bucket objects through file paths. It covers cache sizing, training performance, checkpoint write safety, and cost diagnosis on GKE, Compute Engine, and Cloud Run.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Access training data through file paths
• Choose between FUSE, native reads, and shared file systems
• Check checkpoint and concurrent write safety

Run concurrent Omnigent conversations with real hosts and runners while replacing the LLM with a zero-latency mock. Read the generated report to explain response-time distributions, throughput, and failures, helping assess Omnigent's own processing overhead.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Measuring performance with concurrent hosts
• Studying latency as conversation history grows
• Comparing throughput and failures under load

Compare batching, request scheduling, and memory management for a single model serving instance. Assess concurrent request capacity, response times, generation speed, and GPU time per result that meets the required quality and deadline.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Comparing batching and request scheduling options
• Checking memory capacity for concurrent requests
• Assessing cache reuse and offloading tradeoffs