memory-interfaces

Expert skill for on-chip and external memory interface design in FPGAs

509 stars

Best use case

memory-interfaces is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Expert skill for on-chip and external memory interface design in FPGAs

Teams using memory-interfaces should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/memory-interfaces/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/fpga-programming/skills/memory-interfaces/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/memory-interfaces/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How memory-interfaces Compares

Feature / Agentmemory-interfacesStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Expert skill for on-chip and external memory interface design in FPGAs

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Memory Interfaces Skill

## Overview

Expert skill for on-chip and external memory interface design, enabling efficient memory utilization and high-bandwidth data access in FPGA systems.

## Capabilities

- Infer Block RAM correctly (read-first, write-first)
- Design distributed RAM and LUT RAM
- Configure ECC for memory protection
- Implement memory access controllers
- Interface with DDR memory controllers
- Optimize memory bandwidth utilization
- Design memory arbitration logic
- Handle memory initialization

## Target Processes

- memory-interface-design.js
- ip-core-integration.js
- hardware-software-codesign.js

## Usage Guidelines

### Block RAM Inference
- Use synchronous read/write patterns
- Specify read-first or write-first mode
- Apply ram_style attribute when needed
- Consider true dual-port vs simple dual-port
- Initialize with $readmemh for COE files

### Distributed RAM
- Use for small, shallow memories
- Asynchronous read capability
- Lower latency than Block RAM
- Use for FIFOs, small lookup tables
- Apply ram_style="distributed" attribute

### ECC Implementation
- Enable for reliability-critical data
- Understand SECDED capabilities
- Handle ECC error reporting
- Consider performance impact
- Implement error injection for testing

### DDR Interface
- Use vendor memory controller IP
- Configure timing parameters correctly
- Implement user interface logic
- Handle calibration and initialization
- Design for memory bandwidth requirements

### Memory Arbitration
- Round-robin for fairness
- Priority-based for critical paths
- Implement request queuing
- Handle backpressure properly
- Consider burst efficiency

## Dependencies

- Memory controller IP knowledge
- FPGA memory architecture understanding
- DDR specification awareness

Related Skills

Memory Allocator

509
from a5c-ai/babysitter

Expert skill for custom memory allocator design optimized for language runtime needs

unified-memory

509
from a5c-ai/babysitter

Expert skill for CUDA Unified Memory and memory prefetching optimization. Configure managed memory allocations, implement memory prefetch strategies, handle page fault analysis, configure memory hints and advise, profile unified memory migration, optimize for oversubscription scenarios, and compare managed vs explicit memory.

gpu-memory-analysis

509
from a5c-ai/babysitter

Specialized skill for GPU memory hierarchy analysis and optimization. Analyze memory access patterns, detect bank conflicts, optimize cache utilization, profile global memory bandwidth, and generate optimized memory access code patterns.

memory-analysis

509
from a5c-ai/babysitter

Embedded memory analysis, optimization, and leak detection

memory-model-analyzer

509
from a5c-ai/babysitter

Analyze programs under various memory models for concurrent correctness

memory-leak-detector

509
from a5c-ai/babysitter

Detect memory leaks in desktop applications through heap analysis and object tracking

electron-memory-profiler

509
from a5c-ai/babysitter

Profile Electron app memory usage, detect leaks, analyze renderer process memory, and optimize memory consumption

zep-memory-integration

509
from a5c-ai/babysitter

Zep memory server integration for long-term conversation memory and user profiling

redis-memory-backend

509
from a5c-ai/babysitter

Redis backend for conversation state persistence and caching

memory-summarization

509
from a5c-ai/babysitter

Conversation summarization for memory compression and context management

langchain-memory

509
from a5c-ai/babysitter

LangChain memory integration including ConversationBufferMemory, ConversationSummaryMemory, and vector-based memory

entity-memory-extraction

509
from a5c-ai/babysitter

Entity and fact extraction for user profiling and personalization