Memory Interleaving: Parallel Memory Access

What is Memory Interleaving?

Memory interleaving is a technique that distributes consecutive memory addresses across multiple independent memory banks or channels. Instead of storing sequential addresses in the same memory bank (which would require sequential access), interleaving spreads them across different banks that can be accessed in parallel.

This fundamental optimization technique is crucial for achieving high memory bandwidth in modern computer systems, from desktop DDR5 configurations to high-end GPU memory subsystems.

Why Memory Interleaving Matters

Modern processors can execute instructions much faster than memory can supply data. This creates the "memory wall" - a fundamental bottleneck in computer performance. Memory interleaving helps break through this wall by:

1. Enabling Parallel Access: Multiple memory operations can occur simultaneously across different banks
2. Hiding Access Latency: While one bank is being accessed, others can prepare for upcoming requests
3. Maximizing Bandwidth Utilization: Keeps more of the available memory bandwidth busy
4. Reducing Contention: Spreads access patterns to avoid bank conflicts

Interactive Demonstration

Explore how memory interleaving works in practice with this interactive visualization:

How Memory Addressing Works

Memory interleaving uses a simple but powerful addressing scheme:

For example, with 4-way interleaving:

• Address 0x000 → Bank 0, Offset 0
• Address 0x001 → Bank 1, Offset 0
• Address 0x002 → Bank 2, Offset 0
• Address 0x003 → Bank 3, Offset 0
• Address 0x004 → Bank 0, Offset 1
• Address 0x005 → Bank 1, Offset 1

This distribution ensures that sequential accesses hit different banks, enabling parallelism.

Real-World Examples

DDR5 Memory Systems

Modern DDR5 memory demonstrates the power of interleaving:

• Single Channel: 48 GB/s bandwidth @ 15ns latency
• Dual Channel (2-way): 96 GB/s bandwidth @ 15ns latency
• Quad Channel (4-way): 192 GB/s bandwidth @ 15ns latency

Notice how bandwidth scales linearly with the number of channels, while latency remains constant. This is the key benefit of interleaving - more bandwidth without increased latency.

GPU Memory Architecture

High-end GPUs push interleaving to the extreme:

• GDDR6 (RTX 3070): 4-way interleaving → 256 GB/s
• GDDR6 (RTX 3080): 10-way interleaving → 760 GB/s
• GDDR6X (RTX 4090): 12-way interleaving → 1008 GB/s (over 1 TB/s!)

These massive bandwidth numbers are only possible through aggressive memory interleaving combined with high-speed memory technologies.

Types of Interleaving

1. Low-Order Interleaving

The most common type, where consecutive addresses are distributed round-robin across banks (as shown in our visualization). This is optimal for sequential access patterns.

2. High-Order Interleaving

Uses higher-order address bits to determine the bank. Better for certain structured access patterns but less common in practice.

3. Mixed/Hybrid Interleaving

Combines multiple interleaving schemes to optimize for different access patterns. Modern memory controllers often implement sophisticated hybrid schemes.

Performance Implications

Memory interleaving can provide:

• Up to N× bandwidth improvement with N-way interleaving for sequential access
• Reduced average latency for random access patterns
• Better utilization of available memory channels
• Improved scalability for multi-core systems

However, the actual improvement depends on:

• Access patterns (sequential vs. random)
• Bank conflicts (multiple accesses to the same bank)
• Memory controller efficiency
• Cache behavior

Connection to Modern Computing

Memory interleaving is fundamental to:

1. CPU Performance: Multi-channel DDR4/DDR5 configurations in desktops and servers
2. GPU Computing: Massive parallelism requires extreme memory bandwidth
3. AI/ML Workloads: Training large models is often memory-bandwidth bound
4. High-Performance Computing: Scientific simulations need sustained memory throughput
5. Game Consoles: PS5 and Xbox Series X use sophisticated memory interleaving

Best Practices

When optimizing for interleaved memory:

1. Align data structures to avoid bank conflicts
2. Use sequential access patterns when possible
3. Consider memory stride in multi-dimensional arrays
4. Profile memory access patterns to identify bottlenecks
5. Leverage hardware prefetchers which work well with interleaving

Related Concepts

Understanding memory interleaving is enhanced by familiarity with these related concepts:

Memory Architecture

• Cache Hierarchy: L1/L2/L3 caches and how interleaving affects cache line fills
• Memory Controllers: How controllers manage channel interleaving and scheduling
• NUMA Architecture: Non-uniform memory access in multi-socket systems

Performance Optimization

• Bank Conflicts: Understanding and avoiding simultaneous access to the same bank
• Memory Coalescing: Especially important in GPU programming for warp efficiency
• Prefetching: How hardware prefetchers work with interleaved memory layouts
• Memory Access Patterns: Sequential vs strided access impact on performance

System Design

• Virtual Memory: Page-level interleaving and TLB considerations
• DMA & Memory Mapping: Direct memory access patterns with interleaving
• Memory Bandwidth vs. Latency: The fundamental trade-off in memory system design

Programming Considerations

• Data Structure Alignment: Aligning data to avoid bank conflicts
• Access Pattern Optimization: Sequential vs. strided memory access
• Cache-Aware Algorithms: Designing algorithms that work well with interleaved memory

Conclusion

Memory interleaving is a foundational technique that enables modern computing performance. By understanding how it works, developers can write more efficient code that better utilizes available memory bandwidth. Whether you're optimizing CPU code, writing GPU kernels, or designing hardware systems, memory interleaving principles remain crucial for achieving peak performance.