custom-allocators
Custom allocator skill for memory allocation strategies. Use when implementing…
Intel VTune and AMD uProf profiling skill for microarchitecture analysis. Use when analyzing hotspots, microarchitecture bottlenecks, memory access patterns, pipeline stalls, or using the roofline model. Covers VTune Community Edition (free) and AMD uProf as a free alternative.
$ npx -y skills add mohitmishra786/low-level-dev-skills --skill intel-vtune-amd-uprof --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/intel-vtune-amd-uprofContext preview
The summary Claude sees to decide when to auto-load this skill.
Intel VTune and AMD uProf profiling skill for microarchitecture analysis. Use when analyzing hotspots, microarchitecture bottlenecks, memory access patterns, pipeline stalls, or using the roofline model. Covers VTune Community Edition (free) and AMD uProf as a free alternative.
name: intel-vtune-amd-uprof description: Intel VTune and AMD uProf profiling skill for microarchitecture analysis. Use when analyzing hotspots, microarchitecture bottlenecks, memory access patterns, pipeline stalls, or using the roofline model. Covers VTune Community Edition (free) and AMD uProf as a free alternative. Activates on queries about VTune, uProf, microarchitecture analysis, pipeline stalls, memory bandwidth, roofline model, or hardware performance analysis.
Guide agents through CPU microarchitecture profiling with Intel VTune Profiler (free Community Edition) and AMD uProf: hotspot identification, microarchitecture analysis, memory access pattern optimization, pipeline stall diagnosis, and roofline model analysis.
# Download Intel VTune Profiler (Community Edition — free) # https://www.intel.com/content/www/us/en/developer/tools/oneapi/vtune-profiler.html # Install on Linux source /opt/intel/oneapi/vtune/latest/env/vars.sh # CLI usage vtune -collect hotspots ./prog vtune -collect microarchitecture-exploration ./prog vtune -collect memory-access ./prog # View results in GUI vtune-gui & # File → Open Result → select .vtune directory # Or use amplxe-cl (legacy CLI) amplxe-cl -collect hotspots ./prog amplxe-cl -report hotspots -r result/
| Analysis | What it finds | When to use | |----------|--------------|-------------| | Hotspots | CPU-bound functions | First step — find where time is spent | | Microarchitecture Exploration | IPC, pipeline stalls, retired instructions | After hotspot — why is the hotspot slow? | | Memory Access | Cache misses, DRAM bandwidth, NUMA | Memory-bound code | | Threading | Lock contention, parallel efficiency | Multithreaded code | | HPC Performance | Vectorization, memory, roofline | HPC / scientific code | | I/O | Disk and network bottlenecks | I/O-bound code |
# Collect and report hotspots vtune -collect hotspots -result-dir hotspots_result ./prog # Report top functions by CPU time vtune -report hotspots -r hotspots_result -format csv | head -20 # CLI output example: # Function CPU Time Module # compute_fft 4.532s libfft.so # matrix_mult 2.108s prog # parse_input 0.234s prog
Build with debug info for meaningful symbols:
gcc -O2 -g ./prog.c -o prog # symbols visible in VTune gcc -O2 -g -gsplit-dwarf -fno-omit-frame-pointer ./prog.c -o prog # better stacks
vtune -collect microarchitecture-exploration -r micro_result ./prog vtune -report summary -r micro_result
Key metrics to examine:
| Metric | Meaning | Good value | |--------|---------|-----------| | IPC (Instructions Per Clock) | How many instructions retire per cycle | x86: aim for > 2.0 | | CPI (Clocks Per Instruction) | Inverse of IPC | Lower is better | | Bad Speculation | Branch mispredictions | < 5% | | Front-End Bound | Instruction decode bottleneck | < 15% | | Back-End Bound | Execution unit or memory stall | < 30% | | Retiring | Useful work fraction | > 70% ideal | | Memory Bound | % cycles waiting for memory | < 20% |
Pipeline Analysis (Top-Down Methodology):
├── Retiring (good, useful work)
├── Bad Speculation (branch mispredictions)
├── Front-End Bound
│ ├── Fetch Latency (I-cache misses, branch mispredicts)
│ └── Fetch Bandwidth
└── Back-End Bound
├── Memory Bound
│ ├── L1 Bound → L1 cache misses
│ ├── L2 Bound → L2 cache misses
│ ├── L3 Bound → L3 cache misses
│ └── DRAM Bound → main memory bandwidth limited
└── Core Bound → ALU/compute bound# Collect memory access profile vtune -collect memory-access -r mem_result ./prog # Key output sections: # - Memory Bound: % time waiting for memory # - LLC (Last Level Cache) Miss Rate # - DRAM Bandwidth: GB/s achieved vs theoretical peak # - NUMA: cross-socket accesses (for multi-socket systems)
Reading DRAM bandwidth:
DRAM Bandwidth: 18.4 GB/s Peak Theoretical: 51.2 GB/s Utilization: 36% — likely not DRAM-bound
If DRAM-bound: optimize data layout (AoS → SoA), reduce working set, improve spatial locality.
# Download AMD uProf # https://www.amd.com/en/developer/uprof.html # CLI profiling AMDuProfCLI collect --config tbp ./prog # time-based profiling AMDuProfCLI collect --config assess ./prog # microarchitecture assessment AMDuProfCLI collect --config memory ./prog # memory access # Generate report AMDuProfCLI report -i /tmp/uprof_result/ -o report.html # Open GUI AMDuProf &
AMD uProf metrics map to VTune equivalents:
The roofline model shows whether code is compute-bound or memory-bound by comparing achieved performance against hardware limits:
Performance (GFLOPS/s)
| _______________
Peak | /
Perf | / compute bound
| /
| /
| / memory bandwidth bound
| /
+------------------------------→
Arithmetic Intensity (FLOPS/Byte)# VTune roofline collection vtune -collect hpc-performance -r roofline_result ./prog # Then: VTune GUI → Roofline view # For manual calculation: # Arithmetic Intensity = FLOPS / memory_bytes_accessed
A curated suite of AI agent skills for systems and low-level programming — C/C++, Rust, Zig, GPU, bare-metal firmware, Linux kernel/driver development, computer architecture, compiler internals, HPC, and more.
Repo: mohitmishra786/low-level-dev-skills
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