Frugal Observability

Optimize GPU & CPU Workloads

  • Zero recomplilation
  • Zero instrumentation
  • OpenTelemetry compliant

Optimize the efficiency of your general-purpose and accelerated computing workloads with zymtrace, a continuous profiling solution that provides deep, actionable insights into CPU & GPU-bound applications and inference.

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One zymtrace agent to zym them all!

Frictionless whole-system visibility across all major languages

Drop in zymtrace agent and identify the most expensive lines of code across your entire fleet —your code, third-party libs, interpreted or native, running on CPU or GPU. If it's using cycles, we help you improve its efficiency.

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Powering efficient AI

Maximize GPU Efficiency

Identify performance bottlenecks across GPUs and AI accelerators by correlating hardware profiles with the CPU code paths that launch them. Works with NVIDIA CUDA and PyTorch.

Reduce mean-time-to dopamine

Curated Insights

Most profilers throw flamegraphs at you and expect you to decode them. zymtrace's "Efficiency IQ" tells you exactly what's happening and shows you precisely what to do about it.

How it works

Zero instrumentation. Super low overhead continuous profiler

Step 1: Easy Installation
Deploy zymtrace in minutes with zero code changes. Available for Docker, Kubernetes, and as a binary.
Step 2: Intelligent Analysis
Our advanced analytics engine processes data to provide actionable insights, recommendations, and potential fixes.
Step 3: Optimize and Save
Implement our suggestions to optimize your system, reduce operational costs, and lower your carbon footprint.
Step 1: Easy Installation Step 2: Intelligent Analysis Step 3: Optimize and Save

Frequently asked questions

Currently, only on-premises version is supported. If you're interested in a SaaS version, please contact us at [email protected]
zymtrace is a whole-system profiler for any application, not just GPU code. While profiling, it automatically checks if the machine has an NVIDIA GPU. If one is present, it also detects CPU operations that launch GPU work and provides performance visibility into their interactions.
Our current focus is on NVIDIA CUDA and PyTorch frameworks. If you have a specific use case for TensorFlow, we'd be happy to discuss it with you. [email protected]
zymtrace is currently limited to Linux machines. We heavily utilize eBPF, which is not yet well-supported on Windows.
zymtrace is designed to operate within a minimal resource footprint, targeting just 1% CPU usage and less than 250MB of RAM. This efficiency allows for 24/7 operation on most workloads without noticeably impacting the profiled systems. For particularly resource-sensitive environments, zymtrace can be configured with lower sampling rates, providing valuable insights while further reducing its performance impact. The agent profiles itself so you can clearly see the overhead.

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zymtrace runs entirely on-premise. 5 minutes is all you need to get it up and running.

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