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Port a Numerical Kernel from CPU to GPU for a CFD Simulator

FreeVerified credential4 weeksExpert

Overview

What this challenge is about.

Receive the existing CFD solver (C++17 + OpenMP, around 8,000 lines, the hot kernel is a 7-point stencil sweep over a 512^3 grid), the validation harness, and access to an A100 80GB testbed. Plan the port: choose between native CUDA, CUDA + cuBLAS for the linear-solve substep, or Kokkos for portability. Implement the stencil kernel using shared-memory tiling (32x32x4 with halo), maximize occupancy without spilling, fuse the boundary-condition update where useful. Validate numerical equivalence per cell within 1e-8 against the CPU baseline. Profile with Nsight Compute: report achieved FP64 throughput, memory-bandwidth utilization, and warp-execution efficiency. Deliver the CUDA kernel + harness, the numerical-validation report, an Nsight Compute report (annotated), and a 6-page handover memo for the simulation-tech lead.

CredentialBlockchain-anchored
ShareableLinkedIn-ready
LanguageEnglish
PaceSelf-paced

The Brief

What you'll do, and what you'll demonstrate.

Port a Navier-Stokes stencil kernel from CPU + OpenMP to CUDA on an A100, hit >=60 percent peak FP64 throughput, and validate per-cell numerical equivalence within 1e-8.

Earning criteria — what you'll demonstrate

  • Port a stencil kernel to CUDA with shared-memory tiling
  • Tune occupancy + register usage without spills
  • Validate per-cell numerical equivalence rigorously
  • Read Nsight Compute output and act on it

Program Fit

Where this fits in your program.

Sharpens the same skills your degree expects you to demonstrate.

Skills

Skills you'll demonstrate.

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Roles this prepares you for.

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One more thing

You can put a credential on your CV by Friday.