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Intel Vtune Amd Uprof

  • 256 installs
  • 155 repo stars
  • Updated June 27, 2026
  • mohitmishra786/low-level-dev-skills

Profile CPU hotspots, cache misses, and thread contention with Intel VTune and AMD uProf before release or when investigating production latency regressions.

About

Teaches low-level performance profiling with Intel VTune and AMD uProf for backend and systems code. Explains sampling methodology, reading flame graphs, interpreting PMU counters, and turning findings into concrete ship-ready optimizations for CLI, API, and SaaS workloads.

  • Intel VTune workflow for hotspot analysis
  • AMD uProf cross-vendor profiling parity
  • Hardware counter and cache-miss interpretation
  • Thread and syscall bottleneck isolation
  • Pre-ship regression baselines against SLOs

Intel Vtune Amd Uprof by the numbers

  • 256 all-time installs (skills.sh)
  • +21 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #146 of 596 Debugging skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/mohitmishra786/low-level-dev-skills --skill intel-vtune-amd-uprof

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Listed on Skillselion
Installs256
repo stars155
Last updatedJune 27, 2026
Repositorymohitmishra786/low-level-dev-skills

What it does

Profile CPU hotspots, cache misses, and thread contention with Intel VTune and AMD uProf before release or when investigating production latency regressions.

Files

SKILL.mdMarkdownGitHub ↗

Intel VTune & AMD uProf

Purpose

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.

Triggers

  • "How do I use Intel VTune to profile my code?"
  • "What are pipeline stalls and how do I reduce them?"
  • "How do I analyze memory bandwidth with VTune?"
  • "What is the roofline model and how do I use it?"
  • "How do I use AMD uProf as a free alternative to VTune?"
  • "My code has good cache hit rates but is still slow"

Workflow

1. VTune setup (free Community Edition)

# 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/

2. Analysis types

AnalysisWhat it findsWhen to use
HotspotsCPU-bound functionsFirst step — find where time is spent
Microarchitecture ExplorationIPC, pipeline stalls, retired instructionsAfter hotspot — why is the hotspot slow?
Memory AccessCache misses, DRAM bandwidth, NUMAMemory-bound code
ThreadingLock contention, parallel efficiencyMultithreaded code
HPC PerformanceVectorization, memory, rooflineHPC / scientific code
I/ODisk and network bottlenecksI/O-bound code

3. Hotspot analysis

# 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

4. Microarchitecture exploration — pipeline stalls

vtune -collect microarchitecture-exploration -r micro_result ./prog
vtune -report summary -r micro_result

Key metrics to examine:

MetricMeaningGood value
IPC (Instructions Per Clock)How many instructions retire per cyclex86: aim for > 2.0
CPI (Clocks Per Instruction)Inverse of IPCLower is better
Bad SpeculationBranch mispredictions< 5%
Front-End BoundInstruction decode bottleneck< 15%
Back-End BoundExecution unit or memory stall< 30%
RetiringUseful 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

5. Memory access analysis

# 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.

6. AMD uProf — free alternative for AMD CPUs

# 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:

  • Retired Instructions → IPC analysis
  • Branch Mispredictions → Bad Speculation
  • L1/L2/L3 Cache Misses → Memory Bound levels
  • Data Cache Accesses → Cache efficiency

7. Roofline model

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
# Peak FLOPS = CPUs × cores × freq × FLOPS_per_cycle_per_core
# Peak BW = from hardware spec (e.g., 51.2 GB/s for DDR4-3200 dual channel)

# likwid-perfctr for manual roofline data (Linux)
likwid-perfctr -C 0 -g FLOPS_DP ./prog          # double-precision FLOPS
likwid-perfctr -C 0 -g MEM ./prog               # memory bandwidth

Related skills

  • Use skills/profilers/hardware-counters for raw PMU event collection with perf stat
  • Use skills/profilers/linux-perf for perf-based profiling on Linux
  • Use skills/low-level-programming/cpu-cache-opt for memory access pattern optimization
  • Use skills/low-level-programming/simd-intrinsics for vectorization to increase FLOPS

Related skills

Debuggingbackendtestingdevops

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