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title: The Accelerator Toolkit: A Review of Profiling and...
description: A comprehensive review of profiling and tracing tools for GPUs, DPUs, and APUs. Covers NVIDIA's Nsight suite, AMD's ROCm toolchain (Omniperf, Omnitrace), Intel...
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og:description: A comprehensive review of profiling and tracing tools for GPUs, DPUs, and APUs. Covers NVIDIA's Nsight suite, AMD's ROCm toolchain (Omniperf, Omnitrace), Intel...
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# The Accelerator Toolkit: A Review of Profiling and Tracing for GPUs and other co-processor

**[eunomia eBPF Blog](https://daily.dev/sources/eunomia)** · 39 min read · 0 upvotes · 0 comments

## Summary

A comprehensive review of profiling and tracing tools for GPUs, DPUs, and APUs. Covers NVIDIA's Nsight suite, AMD's ROCm toolchain (Omniperf, Omnitrace), Intel VTune, and open-source frameworks like HPCToolkit and RenderDoc. Discusses eBPF-based low-overhead approaches such as GPUprobe for production monitoring, DPU-specific telemetry challenges, and APU integrated profiling needs. Compares open-source vs. commercial solutions across feature depth, cross-vendor support, and extensibility. Highlights emerging trends including causal profiling, ML-driven analysis, unified multi-accelerator tracing, and standardized performance interfaces. Identifies persistent challenges: vendor fragmentation, black-box hardware, overhead trade-offs, and lack of cross-device coordination.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://eunomia.dev/blog/2025/04/11/the-accelerator-toolkit-a-review-of-profiling-and-tracing-for-gpus-and-other-co-processor>

## Questions this post answers

### What is the overhead of NVIDIA Nsight Systems when profiling a CUDA application?

Nsight Systems typically slows programs by 2×–10× during a profiling session. It is designed for development and tuning rather than continuous or production use, because it must explicitly start a profiling session and collects detailed CPU-GPU timeline data via the CUDA Profiling Tools Interface (CUPTI). For always-on monitoring, lighter tools like GPUprobe are recommended instead.

_Engineers optimizing CUDA workloads track tool trade-offs like these on daily.dev._

### What is GPUprobe and how does it monitor CUDA applications without instrumentation?

GPUprobe is a Linux eBPF-based GPU observability tool that uses uprobes to hook into NVIDIA's CUDA runtime library functions at the kernel level. It monitors events like cudaMalloc/free and kernel launches in real time without modifying the target application. Overhead is measured under 4% in benchmarks, making it suitable for continuous production use. It exports metrics in OpenMetrics format for Prometheus and Grafana dashboards.

_Teams running GPU services in production find continuous monitoring approaches like this on daily.dev._

### What GPU profiling tools did AMD introduce in ROCm 6.2?

AMD introduced Omniperf and Omnitrace in ROCm 6.2. Omniperf is a kernel-level profiler for HPC and ML workloads on AMD Instinct GPUs, offering detailed hardware counter analysis via CLI or GUI dashboard. Omnitrace is a multi-purpose CPU and GPU profiling tool supporting dynamic binary instrumentation, call-stack sampling, and causal profiling for heterogeneous CPU-GPU applications. Both are open-source.

_Developers targeting AMD Instinct GPUs stay current on ROCm toolchain changes through daily.dev._

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---

Tags: [#linux](https://daily.dev/tags/linux), [#cuda](https://daily.dev/tags/cuda)

[View this post on daily.dev](https://daily.dev/posts/the-accelerator-toolkit-a-review-of-profiling-and-tracing-for-gpus-and-other-co-processor-nrwvbot12)

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