Intel-Optimized Memory Architecture Guide

Master memory optimization techniques for Intel Xeon, Core, and Xe GPUs to maximize bandwidth and minimize latency in your applications.

Key Optimization Areas

1. Cache Hierarchy

Optimize line fetches for L1-L3 cache alignment
Use __attribute__((aligned)) for structure packing
Implement false sharing mitigation

2. Memory Bandwidth

Utilize non-temporal writes for streaming data
Use _mm_stream_ps() for bulk memory stores
Align arrays to 64-byte boundaries

3. NUMA Awareness

Use libnuma for node-specific allocations
Place data on local NUMA node
Optimize thread-to-core affinity

4. Prefetching

Use _mm_prefetch() for stream processing
Control temporal locality with _mm_mfence()
Non-temporal stores for bulk data

Code Examples


#include <immintrin.h>

void optimize_data_copy(float* src, float* dst, size_t len) {
  for(size_t i=0; i<len; i += 16) {
    __m512 vec = _mm512_load_ps(src + i);  
    _mm512_stream_ps(dst + i, vec);         // Stream to bypass cache
    _mm512_wait();
  }
}

TIP: Use Intel VTune for Cache Miss Analysis and identify memory hotspots in your applications.

Performance Considerations

Memory Latency

Average memory latency: 85-120ns (DDR5-4800 CL60)

Bandwidth

Peak bandwidth: 560 GB/s with 64-bit AVX512 optimizations

Cache Efficiency

Typical L3 Hit Rate: 89% with optimized packing

Measured in Core i9-14900KS benchmark

DMA Support

Support for RDMA and DirectAccess

Recommended for RDMA over PCIe Gen5

Advanced Techniques

Memory Compression

Use Intel's memory deduplication APIs for large datasets

Hardware Prefetcher

Configure PREFETCHx instructions

Use _mm_prefetcht0 for streaming data
Test with memkind library