AI-Powered Coding
Write optimized CUDA code with intelligent AI assistance tailored for GPU development
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.
- Intelligent CUDA kernel suggestions
- Hardware-aware memory patterns
- Automatic optimization recommendations
- Architecture-specific code completion
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"
- "Refactor this for better occupancy"
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
- Receive performance improvement suggestions
Hardware-Aware Features
Architecture Detection
Automatically detects your GPU architecture and provides tailored suggestions for Turing, Ampere, Ada Lovelace, and Hopper.
Compute Capability Awareness
AI understands your GPU's compute capability and suggests features available for your specific hardware.
Memory Pattern Recognition
Identifies optimal memory access patterns based on your GPU's memory hierarchy and bandwidth characteristics.
Tensor Core Optimization
Suggests tensor core utilization for GPUs that support them, with generation-specific optimizations.
Learn more: See AI Providers to configure your AI models and .rightnowrules to personalize AI behavior.