Open Numerics Discuss your workload
Computational Performance Audit

Find out why your computational code is slow.

We benchmark and profile one computational workload, identify the dominant bottlenecks, and deliver a written technical report with concrete recommendations for making it faster.

Discuss your performance problem See what the report includes

October launch price: $1,500 (standard $2,500) · 2 audits remaining

Performance starts with diagnosis

Don't optimize what isn't limiting you.

Slow computational workflows can have very different causes. The expensive part might be a Python loop, memory access, CPU-GPU communication, an inefficient solver, excessive I/O, poor parallel scaling, or an inefficient algorithm.

The purpose of the Computational Performance Audit is to measure the real bottleneck first, then propose the change.

Software

Implementation bottlenecks

  • Python loops and interpreter overhead
  • Poor memory-access patterns
  • Unnecessary allocations and copies
  • Vectorization opportunities
Hardware

Scaling bottlenecks

  • CPU and GPU utilization
  • Parallel scaling
  • Data-transfer overhead
  • Memory bandwidth
Numerics

Algorithmic bottlenecks

  • Solver choice and convergence
  • Numerical formulation
  • Reduced-order methods
  • Scientific ML surrogates
The main deliverable

You receive a written Computational Performance Report.

We create a technical document that your team can build on. It contains what to fix, how Open Numerics can help, and how to justify the larger engineering effort.

01

Executive Summary

The most important findings in a form that can be shared with technical leadership.

  • What is limiting performance
  • Why it matters
  • Highest-value opportunities
  • Recommended next steps
02

Measured Baseline

A reproducible view of how the workload performs today.

  • Runtime and workload definition
  • Hardware and execution environment
  • Profiler results
  • Memory and scaling behavior
03

Bottleneck Analysis

A technical explanation of where time and compute are being lost.

  • Dominant kernels and operations
  • Software and memory bottlenecks
  • CPU/GPU utilization issues
  • Numerical and algorithmic limitations
04

Prioritized Recommendations

Concrete improvements ranked by expected value and engineering effort.

  • Quick wins
  • Engineering improvements
  • Algorithmic opportunities
  • Expected impact and implementation effort
05

Implementation Options

Specific opportunities your team or Open Numerics can build next.

  • Code-level optimization opportunities
  • Parallel or GPU acceleration
  • Solver and architecture improvements
  • Potential Scientific ML or surrogate approaches
How the audit works

From a slow workload to a clear technical roadmap.

  1. 1

    Define the workload

    We agree on one representative computational workflow, its current performance, and the conditions under which it should be evaluated.

  2. 2

    Benchmark and profile

    We reproduce the workload and measure where runtime, memory, communication and compute are actually being spent.

  3. 3

    Investigate the bottlenecks

    We look beyond individual functions and consider software, hardware, numerical methods and overall workflow architecture.

  4. 4

    Deliver the report

    You receive the written analysis, prioritized recommendations, and implementation options, followed by a technical walkthrough of the findings.

Useful even if we do nothing else

The report belongs to you.

The Computational Performance Audit is a standalone engagement. Your team can use the recommendations internally, hand them to another engineering team, or ask Open Numerics to implement the highest-value improvements.

The goal is to leave you with a clearer understanding of the performance problem and a practical roadmap for solving it.

Start with the bottleneck

What workflow is slowing your team down?

Bring us one slow simulation, numerical workflow, or computational bottleneck. In a free 30-minute technical call, we'll discuss the problem and determine whether a Computational Performance Audit is the right next step. The audit is $1,500 during the October launch, $2,500 afterwards.

Discuss your workload

Prefer email? Write to info@opennumerics.com .