Navigating CPU Architecture Mismatches in HPC: Ice Lake vs. Cascade Lake

The Challenge of Heterogeneous CPU Architectures in HPC

In high-performance computing (HPC) environments, the interplay between login and compute node architectures can significantly impact both system performance and user experience. This post explores the specific challenges posed by differing CPU microarchitectures, using the example of an environment with Intel Xeon Gold 6346 (Ice Lake-SP) login nodes and Intel Xeon Gold 6248R (Cascade Lake-SP Refresh) compute nodes.

Understanding the Architecture Mismatch

Processor Specifications

Component	Login Node (Ice Lake-SP)	Compute Node (Cascade Lake-SP)
Model	Intel Xeon Gold 6346	Intel Xeon Gold 6248R
Base Clock	3.1 GHz	3.0 GHz
Max Clock	3.6 GHz	3.0 GHz
L1d Cache	48K per core	32K per core
L2 Cache	1.25MB per core	1MB per core
Hyper-Threading	Enabled (2 threads/core)	Disabled (1 thread/core)
Logical CPUs	64 (16c × 2 × 2s)	48 (24c × 1 × 2s)

Key Technical Challenges

1. Instruction Set Architecture (ISA) Mismatch

The most critical issue arises from the differing instruction sets between these CPU generations. The Ice Lake architecture introduces several advanced instructions not available in Cascade Lake:

• AVX-512 extensions (avx512ifma, avx512_vbmi2)
• GFNI (Galois Field New Instructions)
• VAES (Vector AES)
• VPCLMULQDQ (Vector Carry-Less Multiplication)

2. The “Illegal Instruction” Problem

When software is compiled on the login node without proper architecture flags, it may utilize these newer instructions, leading to runtime failures on compute nodes:

# Example of a common error when running code with unsupported instructions
Illegal instruction (core dumped)

3. Performance Variability

Even when code runs on both architectures, performance characteristics differ significantly:

• Ice Lake (login node) typically offers higher IPC (Instructions Per Cycle)
• Clock speed differences (3.6GHz vs 3.0GHz)
• Cache size variations affect memory-bound applications
• Hyper-Threading status impacts thread scheduling

Mitigation Strategies

1. Proper Compilation Practices

Users should be educated on proper compilation techniques:

# Target the specific compute node architecture
CFLAGS="-march=cascadelake -mtune=cascadelake"

# Or use a more conservative baseline
CFLAGS="-march=x86-64-v3"

# For CMake projects
cmake -DCMAKE_CXX_FLAGS="-march=cascadelake" ..

2. Environment Modules

Implement architecture-specific module files:

# Load appropriate compiler for Cascade Lake nodes
module load gcc/11.2.0-cascadelake

# Or for Ice Lake nodes
module load gcc/11.2.0-icelake

3. Containerization

Use Singularity or Docker containers with the correct architecture:

# Build container on a compute node
srun --pty -p compute --constraint=cascadelake singularity build myapp.sif myapp.def

System Administration Recommendations

1. Standardize Build Environments

   • Provide build nodes matching compute node architecture
   • Document architecture-specific compilation guidelines

2. Software Stack Management

   • Maintain separate module paths for different architectures
   • Use EasyBuild or Spack for architecture-aware software builds

3. User Education

   • Train users on cross-compilation techniques
   • Provide architecture detection scripts
   • Document performance characteristics

4. Monitoring and Testing

   • Implement CI/CD pipelines that test on target architectures
   • Monitor for illegal instruction errors in job logs

Performance Considerations

Workload Characteristic	Impact	Mitigation
Memory-bound	High (cache differences)	Optimize memory access patterns
CPU-bound	Medium (IPC differences)	Use architecture-specific optimizations
Vectorized	Very High (ISA differences)	Compile with appropriate flags
Multi-threaded	High (HT differences)	Tune thread affinity and binding

Conclusion

Managing heterogeneous CPU architectures in HPC environments requires careful planning and user education. By implementing the strategies outlined above, system administrators can minimize compatibility issues while maintaining performance across different node types. The key is to establish clear guidelines for software development and deployment that account for architectural differences between login and compute nodes.

For users, the most important practice is to always test production workloads on the target architecture rather than relying on login node performance or behavior.

Further Reading

1. Intel® 64 and IA-32 Architectures Software Developer Manuals
2. GCC x86 Options
3. HPC Software Stack Management Best Practices