AccelProf

A Modular Program Analysis Tool Framework for Emerging Accelerators.

AccelProf is a modular program analysis framework for accelerator workloads spanning NVIDIA CUDA, AMD ROCm, and modern deep-learning systems. It abstracts over heterogeneous profiling APIs and deep-learning frameworks, providing a unified interface for capturing and analyzing runtime events at multiple levels. Its extensible architecture enables researchers and practitioners to rapidly prototype custom analysis tools with minimal overhead.

# Download
git clone --recursive https://github.com/AccelProf/AccelProf.git
git submodule update --init --recursive

# Build and install
#   DEBUG=1: enable debug symbols (-g)
#   OPT_LVL=0|1|2|3: compiler optimization level
#   ENABLE_CS=1: enable Compute Sanitizer backend
#   ENABLE_NVBIT=1: enable NVBit backend
#   ENABLE_TORCH=1: enable PyTorch profiling
#   ENABLE_ROCM=1: enable ROCm backend
make \
    DEBUG=0 \
    OPT_LVL=0 \
    ENABLE_CS=0 \
    ENABLE_NVBIT=0 \
    ENABLE_TORCH=0 \
    ENABLE_ROCM=0


# Set env
export ACCEL_PROF_HOME=$(pwd)
export PATH=${ACCEL_PROF_HOME}/bin:${PATH}

Analyze an accelerator application:

accelprof -v -t app_analysis <executable> [args...]

Full user and developer documentation: 👉 https://accelprofdocs.readthedocs.io

• [CGO’26] PASTA: A Modular Program Analysis Tool Framework for Accelerators.
  Mao Lin, Hyeran Jeon, and Keren Zhou.
  Proceedings of the 23rd ACM/IEEE International Symposium on Code Generation and Optimization (CGO 2026).

Released under the MIT License. See LICENSE for details.