diff --git a/docs_amd/examples/rocopt-example.rst b/docs_amd/examples/rocopt-example.rst index 8079b994c6..eaf6bf7428 100644 --- a/docs_amd/examples/rocopt-example.rst +++ b/docs_amd/examples/rocopt-example.rst @@ -8,7 +8,7 @@ rocOpt examples ******************************************************************** -The rocOpt examples can be found in GitHub under the https://github.com/AMD-Ecosystem/rocopt/tree/amd-integration/examples_notebook folder. +The rocOpt examples can be found in GitHub under the https://github.com/AMD-Ecosystem/rocOpt/tree/release/rocopt-26.07 folder. The examples include the following three notebooks to demonstrate vehicle routing problems, large-scale linear programming, and mixed-integer linear programming. @@ -47,7 +47,7 @@ Vehicle routing problem notebook (``cvrptw_benchmark_rocopt.ipynb``) A 1000-customer Gehring & Homberger CVRPTW instance (``C1_10_1``, best known cost 42 478.95 with 100 vehicles). Restart the kernel and run all cells. -The single solve is capped at 60 s for demo runtime; the upstream NVIDIA +The single solve is capped at 60 s for demo runtime; the upstream notebook chains a 10 s + 120 s pair. Run-to-run variance of a few percent is expected. cuOpt's routing solver is @@ -62,7 +62,7 @@ through the algebraic-modeling Python API. The solver method is pinned to **PDLP only** (``method=1``) on rocopt. The default ``method=0`` (Concurrent) launches a Barrier solver thread alongside -PDLP, but Barrier requires cuDSS, which is NVIDIA-only. On rocopt the missing +PDLP, but Barrier requires cuDSS, which is not currently supported on ROCm. On rocopt the missing dispatcher path can deadlock a re-solve of the same ``Problem`` object — most visibly in the MILP notebook, which solves the LP relaxation twice. @@ -288,32 +288,3 @@ directory: rocopt:amd-integration Then launch Jupyter with ``--notebook-dir /workspace/examples_notebook``. - -Per-notebook details ---------------------- - -The following provide specific details for two of the notebooks. - -Routing benchmark (``cvrptw_benchmark_rocopt.ipynb``) -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -A 1000-customer Gehring & Homberger CVRPTW instance (``C1_10_1``, best known -cost 42 478.95 with 100 vehicles). Restart the kernel and run all cells. -The single solve is capped at 60 s for demo runtime; the upstream NVIDIA -notebook chains a 10 s + 120 s pair. - -Run-to-run variance of a few percent is expected. cuOpt's routing solver is -a randomized parallel local-search metaheuristic; identical inputs do not -produce bit-identical outputs across GPU runs. - -Diet optimization (``diet_optimization_lp.ipynb`` and ``..._milp.ipynb``) -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -Solve the classic USDA diet LP (and an MILP variant with integer servings) -through the algebraic-modeling Python API. - -The solver method is pinned to **PDLP only** (``method=1``) on rocopt. The -default ``method=0`` (Concurrent) launches a Barrier solver thread alongside -PDLP, but Barrier requires cuDSS, which is NVIDIA-only. On rocopt the missing -dispatcher path can deadlock a re-solve of the same ``Problem`` object — most -visibly in the MILP notebook, which solves the LP relaxation twice. diff --git a/docs_amd/index.rst b/docs_amd/index.rst index 90151e31da..5f904a89bf 100644 --- a/docs_amd/index.rst +++ b/docs_amd/index.rst @@ -36,7 +36,7 @@ The rocOpt code is open and hosted at * :doc:`rocOpt Examples ` To contribute to the documentation refer to -`Contributing to ROCm-DS `_. +`Contributing to AMD Data Science `_. You can find licensing information on the `Licensing `_ page. diff --git a/docs_amd/what_is_rocopt.rst b/docs_amd/what_is_rocopt.rst index b83b26aa91..adde7a1b6f 100644 --- a/docs_amd/what_is_rocopt.rst +++ b/docs_amd/what_is_rocopt.rst @@ -12,7 +12,7 @@ rocOpt is an open-source, GPU-accelerated engine for decision optimization on AM GPUs through the ROCm software stack. It solves large-scale linear programming (LP), mixed-integer linear programming (MILP), quadratic programming (QP), and vehicle routing problems containing millions of variables and constraints, returning near real-time results on -AMD Instinct MI300X and MI355X GPUs through the ROCm software stack. +AMD Instinct MI300X and MI355X GPUs. rocOpt is aligned with and API-compatible with cuOpt 25.10, so you can run existing cuOpt workloads and optimization pipelines on AMD Instinct GPUs without @@ -48,10 +48,10 @@ the ROCm 7.2.3 runtime. This includes the following features: - Server API — serve optimization requests over HTTP with a cuOpt-compatible interface. -- rocOpt is built on the ROCm Data Science (ROCm-DS) stack — a HIP port +- rocOpt is built on the AMD Data Science stack — a HIP port cuOpt that maps RAPIDS-style dependencies to their ROCm equivalents (hipRAFT, hipMM, rocThrust, hipCUB, rocPRIM, hipSPARSE, hipBLAS, hipSOLVER) so workloads run on - AMD Instinct hardware alongside other ROCm-DS libraries such as hipDF. + AMD Instinct hardware alongside other AMD Data Science libraries such as hipDF. - rocOpt supports concrete decision-optimization use cases where GPU acceleration changes what is tractable in production, including: