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Verifies whether a requested ROCm-DS workflow is officially supported, source-build feasible, or experimental on the target system.
Migrates pandas-like workflows to hipDF and cudf.pandas style acceleration, auditing for unsupported features.
Leverages GPU acceleration to process and analyze complex graph structures using hipGRAPH. Note: hipGRAPH is early access.
Utilizes the HIP Memory Manager (hipMM) for advanced GPU memory pooling, efficient allocation, and data movement.
Utilizes hipRAFT for foundational, reusable GPU-accelerated primitives like clustering, dimensionality reduction, and statistical operations.
Selects, builds, benchmarks, and validates hipVS ANN indexes and query paths for ROCm-DS workloads.
| name | placeholder |
| description | Placeholder skill description. |
| tools | ["bash","python","git"] |
| inputs | ["source_files"] |
| outputs | ["report"] |
| tags | ["rocm","data-science","gpu"] |
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