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AI-Powered CUDA Coding

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Smart Autocomplete

Context-aware CUDA completions with Fill-in-the-Middle (FIM) optimization. Supports 20+ FIM-capable models including DeepSeek R1, Codestral 2501, and StarCoder2.

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Ctrl+K Editing

Select any code and press Ctrl+K to describe changes in natural language:
  • “Optimize this kernel for memory bandwidth”
  • “Add error checking to this CUDA call”
  • “Convert this to use shared memory”

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Chat Integration

Full project context with CUDA-specific knowledge:
  • Ask questions about GPU architecture optimization
  • Get recommendations for specific hardware (Ampere, Ada Lovelace, Hopper)
  • Troubleshoot CUDA compilation and runtime issues

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Real-Time CUDA Profiling

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NVIDIA Nsight Compute Integration

Production-grade profiling using nv-nsight-cu-cli with comprehensive hardware metrics: Core Performance Metrics:
  • SM Efficiency: Streaming Multiprocessor utilization percentage
  • Memory Throughput: Achieved vs theoretical memory bandwidth (GB/s)
  • Occupancy: Active warps vs maximum theoretical warps
  • Warp Efficiency: Percentage of active threads in executed warps
  • Instruction Replay Overhead: Pipeline stall analysis
  • Global Memory Efficiency: Coalesced memory access patterns
  • Shared Memory Efficiency: Bank conflict analysis
  • Branch Efficiency: Divergent execution measurement
Advanced Metrics:
  • L1/L2 Cache Hit Rates: Memory hierarchy performance
  • Register Usage: Per-thread register consumption
  • Power Draw: Real-time GPU power consumption (watts)
  • Temperature: GPU thermal monitoring
  • Roofline Analysis: Compute vs memory-bound classification

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Multi-Level Profiling Support

Kernel Profiling

Profile specific __global__ functions with targeted analysis

Application Profiling

Full executable profiling with complete call graphs

CLI Integration

Direct nv-nsight-cu-cli integration with custom metrics

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Visual Profiling Interface

CodeLens Integration:
  • Inline performance metrics displayed above CUDA kernels
  • Real-time execution time, SM efficiency, memory throughput
  • Color-coded performance indicators:

🟢 Green

>80% efficiency (optimized kernels)

🟡 Orange

40-80% efficiency (moderate performance)

🔴 Red

<40% efficiency (needs optimization)
Interactive Profiling Controls:
  • Gutter Play Buttons: One-click profiling from editor margins
  • Dedicated Profiling Panel: Comprehensive results view with historical data
  • Multi-GPU Support: Device switching and cross-GPU analysis
  • Elevated Profiling: Windows UAC support for performance counter access

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Hardware Detection & Monitoring

GPU Hardware Integration:
  • Multi-Vendor Detection: NVIDIA, AMD, Intel, Apple Silicon
  • Real-Time Monitoring: nvidia-smi integration for live metrics
  • Hardware Specifications: Automatic detection of compute capability, SM count, memory specs
  • Architecture Support: Turing, Ampere, Ada Lovelace, Hopper optimizations
CUDA Environment Detection:
  • Toolkit Detection: Automatic CUDA 11.0-12.5 detection
  • Registry Integration: Windows performance counter access
  • Multi-Version Support: Compatible with various NCU versions
  • Diagnostic Capabilities: Comprehensive environment validation

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AI-Powered Performance Analysis

Intelligent Optimization Recommendations:
  • Bottleneck Classification: Memory-bound vs compute-bound identification
  • Architecture-Specific Suggestions: Tailored for detected GPU architecture
  • Performance Trend Analysis: Historical optimization tracking
  • Automated Code Suggestions: AI-generated kernel optimizations based on profiling data

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AI Provider Architecture

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BYOK (Bring Your Own Key) - Free Tier

  • OpenRouter API Key: The only supported BYOK option
  • Get unlimited usage with your own OpenRouter key
  • Access to 200+ models through OpenRouter’s unified API
  • Support for providers: OpenAI, Anthropic, DeepSeek, Mistral, Google, and more

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RightNow Proxy - Pro Tier

  • Managed Service: Pre-configured OpenRouter integration
  • Curated Models: Optimized model selection for CUDA development
  • Usage Tracking: Comprehensive analytics and billing
  • Priority Access: Faster response times and premium models

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Model Routing Architecture

All cloud providers route through OpenRouter for unified access:
  • OpenAI (GPT-4, GPT-4 Turbo) → OpenRouter → OpenAI
  • Anthropic (Claude 3.5 Sonnet, Claude 3 Opus) → OpenRouter → Anthropic
  • DeepSeek (R1 series) → OpenRouter → DeepSeek
  • Mistral (Codestral, Mistral Large) → OpenRouter → Mistral
  • Google (Gemini 2.0 Flash) → OpenRouter → Google

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Local Models (Privacy-First)

Complete offline capability with no data leaving your machine:
  • Ollama: Easy local model management with CUDA acceleration
  • vLLM: High-performance inference server for CUDA GPUs
  • LM Studio: User-friendly local deployment with GPU support

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Hardware Integration

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Automatic GPU Detection

  • NVIDIA GPUs: Full support (GeForce, RTX, Quadro, Tesla, A100, H100)
  • Multi-GPU: Cross-GPU profiling and load balancing analysis
  • CUDA Versions: Support for CUDA Toolkit 11.0-12.5

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Architecture-Aware Intelligence

Tailored suggestions for specific GPU architectures:
  • Turing: Tensor core optimization, RT core utilization
  • Ampere: Sparse tensor operations, structural sparsity
  • Ada Lovelace: Ada shader efficiency, RT generation 3
  • Hopper: Transformer engine, thread block clusters
macOS Support: Coming soon with serverless profiling capabilities