PowerColor Radeon AI PRO R9700 32GB Review
Hier Hermes setup met Lemonade-server voorlopig op Ubuntu 24.04(zover geen compatibility issue meer, e.g MOSS)
4 Sterren omdat third-party frameworks(e.g ComfyUI) geschat nog een half jaartje of minder nodig hebben(2027) om vlekkeloos te werken*
Example bleeding edge & dependency lag:
- PyTorch2.14 @ROCm 7.14, bug ziet maar 16GB => Can not allocate/OOM verschijnselen op bepaalde workflows <20GB VRAM.
De tien jarige jubileum ROCm release AMD@ROCm10.0.0 (version bump 7.4->10.0) vertoont veel voorspoed op dergelijke punten*
Een VRAM knipoog naar de ATi Radeon 9700 Pro 128MB had leuk geweest, maar blijkbaar zijn de MI250+ Instinct kaarten nog hot in DC
Pluspunten
VRAM / LLM Toepassingen Adviesprijs RDNA4 / Pro driver features Zeer progresieve software ontwikkelingen. Stil waneer Idle : ) ROCm en CUDA kunnen prima naast elkaar op één host draaien (venv) PS-PCIe Y Spliter inbegrepen
Minpunten
✦Nightly release ROCm ⇝Dependency lag* Tensorflow optimalisatie
Eindoordeel
*ROCm10.0.0 (version bump 7.4->10.0)
Single Source Tree: All ROCm repositories (HIP, rocBLAS, MIOpen, rocFFT, rocRAND, Thrust, rocPRIM, etc.) unified into one consolidated codebase rather than 10+ separate Git repos with independent versioning schemes.
Unified Build System: Single automated pipeline that compiles all ROCm components together from the single source tree, eliminating cross-repo build conflicts and version mismatches.
Declarative Dependency Graph: TheRock knows the exact dependency chain—which components depend on which others—and automatically sequences builds to satisfy dependencies without manual intervention.
Multi-Platform Validation: Automated testing across Windows, Linux, Instinct accelerators, Radeon GPUs, and Ryzen integrated graphics in parallel—not sequentially.
Integrated CI/CD: Continuous integration where code changes to any component trigger immediate testing against all dependent layers and target platforms; failures block the pipeline before proceeding.
Staged Release Queue: Components move through the pipeline together—no component ships until the entire stack passes validation on all supported platforms and hardware families.
Regression Detection: Automated performance and correctness benchmarks catch regressions across all GPU families and OS platforms before release; includes microbenchmarks and end-to-end workload testing.
Framework Wheel Testing: PyTorch, TensorFlow, and other framework wheels are tested against the core libraries in the same validation cycle, not afterward; real-world model inference/training is validated pre-release.
Single Version Number: All ROCm components ship at the same version (10.0.0, etc.) because they've all been validated together—no mismatched library versions in the field.
Artifact Caching & Reuse: Build outputs from earlier stages are cached and reused in dependent stages, reducing total pipeline time and ensuring consistency across the entire build.
Automated Release Packaging: Once the full stack passes validation, TheRock automatically generates release packages, documentation, and checksums for all platforms simultaneously.
Single Source Tree: All ROCm repositories (HIP, rocBLAS, MIOpen, rocFFT, rocRAND, Thrust, rocPRIM, etc.) unified into one consolidated codebase rather than 10+ separate Git repos with independent versioning schemes.
Unified Build System: Single automated pipeline that compiles all ROCm components together from the single source tree, eliminating cross-repo build conflicts and version mismatches.
Declarative Dependency Graph: TheRock knows the exact dependency chain—which components depend on which others—and automatically sequences builds to satisfy dependencies without manual intervention.
Multi-Platform Validation: Automated testing across Windows, Linux, Instinct accelerators, Radeon GPUs, and Ryzen integrated graphics in parallel—not sequentially.
Integrated CI/CD: Continuous integration where code changes to any component trigger immediate testing against all dependent layers and target platforms; failures block the pipeline before proceeding.
Staged Release Queue: Components move through the pipeline together—no component ships until the entire stack passes validation on all supported platforms and hardware families.
Regression Detection: Automated performance and correctness benchmarks catch regressions across all GPU families and OS platforms before release; includes microbenchmarks and end-to-end workload testing.
Framework Wheel Testing: PyTorch, TensorFlow, and other framework wheels are tested against the core libraries in the same validation cycle, not afterward; real-world model inference/training is validated pre-release.
Single Version Number: All ROCm components ship at the same version (10.0.0, etc.) because they've all been validated together—no mismatched library versions in the field.
Artifact Caching & Reuse: Build outputs from earlier stages are cached and reused in dependent stages, reducing total pipeline time and ensuring consistency across the entire build.
Automated Release Packaging: Once the full stack passes validation, TheRock automatically generates release packages, documentation, and checksums for all platforms simultaneously.
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Reacties (1)
Interessant als je zou melden welk model je nu draait als je 'daily driver' en wat aantal tok/s is (decode), evt. ook prefill erbij zetten.
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