AI-Assisted Performance Engineering

Compute at full throttle.

Energy Objects, Inc. treats GPU/HPC performance and applied AI as one discipline, not two — helping organizations design, build, and optimize high-performance computing and AI systems, turning idle silicon into scientific insight and business value.

What we do

Services built for serious compute

HPC Consulting

Architecture reviews, cluster and cloud strategy, scheduler and storage design, and procurement guidance. We help you size, build, and operate compute environments that match your workloads — on-prem, cloud, or hybrid.

  • Cluster & cloud architecture
  • Workload characterization
  • Scheduler & storage tuning

AI & Machine Learning

From feasibility studies to production pipelines: model selection, training at scale, inference optimization, and integrating AI into scientific and engineering workflows — grounded in what the data and physics actually support.

  • ML for scientific workflows
  • Distributed training & inference
  • GPU pipeline engineering

Software Development & Optimization

We write, modernize, and accelerate performance-critical code. Profiling-driven optimization, parallelization with MPI, OpenMP, and CUDA, and modernization of legacy Fortran and C/C++ into maintainable, fast software.

  • Profiling-driven acceleration
  • GPU porting (CUDA / HIP / SYCL)
  • Legacy code modernization

Why it matters

Performance is a business outcome

Every hour a simulation runs is an hour of cluster cost, energy spend, and delayed decisions. Optimization compounds: a faster kernel means more design iterations, finer models, shorter turnaround — and often a smaller hardware bill.

We measure first, then engineer. Roofline analysis, hotspot profiling, and scaling studies tell us where the time goes; targeted engineering gets it back.

  • Shorter time-to-result for simulation and training
  • Lower cost per job on cloud and on-prem
  • Codes that scale with your next machine, not against it
Typical engagement: wall-clock runtime
Before
14.2 h
Tuned
5.4 h
GPU port
76 min

Illustrative results — actual gains depend on the workload.

Where we work

Deep expertise across the stack

Rooted in energy-sector computing — seismic imaging, reservoir simulation, engineering analysis — and applicable anywhere performance is the product.

CUDA / HIP / SYCL MPI & OpenMP Seismic Imaging Reservoir Simulation CFD & FEA Fortran Modernization C / C++ / Python Distributed Training LLM Integration Model Context Protocol (MCP) Claude API & Agent SDK Slurm / PBS Cloud HPC (AWS · Azure · GCP) Profiling & Roofline Analysis Parallel I/O Containers & CI for HPC

How we engage

A measured path from audit to handoff

  1. Assess

    We profile your workloads and review your environment to find where time, money, and energy actually go.

  2. Design

    A concrete plan with predicted gains, costs, and risks — so you approve engineering, not guesswork.

  3. Build & Optimize

    Short iterations, benchmarked at every step. Correctness is verified against your reference results.

  4. Transfer

    Documentation, tests, and working sessions so your team owns the result — no black boxes, no lock-in.

0+ Years of HPC engineering
0× Speedups delivered on key kernels
0% Typical compute cost reduction
0% Knowledge transferred, always

Get in touch

Let’s make your compute count

Tell us about your workload — a slow simulation, an AI initiative, a cluster decision — and we’ll tell you what’s possible.

info@energyobjects.com