Physics, Math, Codeprogramming, MVP design+Mr. Pavl Mazniker
Product Requirement Document (PRD)
Product Vision:
<YOUR REQUIREMENTS AND SPECS>
Features:
<YOUR REQUIREMENTS AND SPECS>
Workflow:
<YOUR REQUIREMENTS AND SPECS>
Wireframes for key product
screens:
<YOUR REQUIREMENTS AND SPECS>
Dashboard:
<YOUR REQUIREMENTS AND SPECS>
Modules:
<YOUR REQUIREMENTS AND SPECS>
Onboarding:
<YOUR REQUIREMENTS AND SPECS>
Settings:
<YOUR REQUIREMENTS AND SPECS>
High-level technical architecture:
Recommended tech stack:
<YOUR REQUIREMENTS AND SPECS>
System structure:
<YOUR REQUIREMENTS AND SPECS>
Architecture
Diagram:
<YOUR REQUIREMENTS AND SPECS>
Integrations:
<YOUR REQUIREMENTS AND SPECS>
MVP roadmap:
<YOUR REQUIREMENTS AND SPECS>
Prioritized features:
User Cases:
<YOUR REQUIREMENTS AND SPECS>
Acceptance Criterias
for Developers:
<YOUR REQUIREMENTS AND SPECS>
Development phases+Product Planning Phases:
<YOUR REQUIREMENTS AND SPECS>
Blackwell‑Optimised
Diffusion Engine & Perf Harness
A
production‑grade CUDA solver bundle targeting Blackwell‑class
GPUs, combining:
Performance test harness
– runs a suite of 3D grid sizes, measures sec/step, points/s, and
device memory usage, and emits a CSV (perf_results.csv) for
reproducible benchmarks.
Mixed‑precision diffusion
kernels – FP16 field storage with FP32 accumulation to
unlock ~1.5–3× higher throughput vs FP32‑only, without
giving up stability.
Geometric multigrid V‑cycle
– shared‑memory smoother and multilevel hierarchy to replace
Jacobi in implicit diffusion solves and cut iteration counts by
~5–20×.
Integration hooks + script –
ready‑to‑paste TuringSolver entry points and a
one‑command perf suite script to build, run, and compare on the
Blackwell SKU.
Position this as a discrete, license‑ready
bundle for GPU vendors, cloud HPC teams, or simulation OEMs who want
provable Blackwell‑class performance out of the box.
Mr. Pavl's other services
Physics, Math, Codeprogramming, MVP design+Mr. Pavl Mazniker
Starting at$35 /hr
Tags
Components
Modules
Product Requirement Document (PRD)
Product Vision:
<YOUR REQUIREMENTS AND SPECS>
Features:
<YOUR REQUIREMENTS AND SPECS>
Workflow:
<YOUR REQUIREMENTS AND SPECS>
Wireframes for key product
screens:
<YOUR REQUIREMENTS AND SPECS>
Dashboard:
<YOUR REQUIREMENTS AND SPECS>
Modules:
<YOUR REQUIREMENTS AND SPECS>
Onboarding:
<YOUR REQUIREMENTS AND SPECS>
Settings:
<YOUR REQUIREMENTS AND SPECS>
High-level technical architecture:
Recommended tech stack:
<YOUR REQUIREMENTS AND SPECS>
System structure:
<YOUR REQUIREMENTS AND SPECS>
Architecture
Diagram:
<YOUR REQUIREMENTS AND SPECS>
Integrations:
<YOUR REQUIREMENTS AND SPECS>
MVP roadmap:
<YOUR REQUIREMENTS AND SPECS>
Prioritized features:
User Cases:
<YOUR REQUIREMENTS AND SPECS>
Acceptance Criterias
for Developers:
<YOUR REQUIREMENTS AND SPECS>
Development phases+Product Planning Phases:
<YOUR REQUIREMENTS AND SPECS>
Blackwell‑Optimised
Diffusion Engine & Perf Harness
A
production‑grade CUDA solver bundle targeting Blackwell‑class
GPUs, combining:
Performance test harness
– runs a suite of 3D grid sizes, measures sec/step, points/s, and
device memory usage, and emits a CSV (perf_results.csv) for
reproducible benchmarks.
Mixed‑precision diffusion
kernels – FP16 field storage with FP32 accumulation to
unlock ~1.5–3× higher throughput vs FP32‑only, without
giving up stability.
Geometric multigrid V‑cycle
– shared‑memory smoother and multilevel hierarchy to replace
Jacobi in implicit diffusion solves and cut iteration counts by
~5–20×.
Integration hooks + script –
ready‑to‑paste TuringSolver entry points and a
one‑command perf suite script to build, run, and compare on the
Blackwell SKU.
Position this as a discrete, license‑ready
bundle for GPU vendors, cloud HPC teams, or simulation OEMs who want
provable Blackwell‑class performance out of the box.
Mr. Pavl's other services
$35 /hr