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Add ROCm-Finance content to docs
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| # ROCm-Finance Blogs | ||
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| This page contains a list of blog posts related to the AMD ROCm™ Finance Toolkit (ROCm-Finance) | ||
| and its individual components. See [ROCm Blogs](https://rocm.blogs.amd.com/) for | ||
| blogs related to all AMD and ROCm products. | ||
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| ::::{grid} 2 2 3 4 | ||
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| :::{grid-item-card} | ||
| :padding: 1 | ||
| :img-top: ../images/rocm-finance.png | ||
| :class-img-top: small-sd-card-img-top | ||
| :class-body: small-sd-card | ||
| :class: small-sd-card | ||
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| <a href="https://rocm.blogs.amd.com/ecosystems-and-partners/rocm-finance/README.html" class="card-header-link"> | ||
| <h2 class="card-header">Using Gradient Boosting Libraries on MI300X for Financial Risk Prediction</h2> | ||
| </a> | ||
| <p class="paragraph"> Financial institutions deal with massive datasets and complex models that demand high computational power. | ||
| With AMD ROCm™ and GPU-accelerated libraries like LightGBM and ThunderGBM, we can significantly reduce training time while improving model performance.</p> | ||
| ::: | ||
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| :::{grid-item-card} | ||
| :padding: 1 | ||
| :img-top: ../images/finance-6.png | ||
| :class-img-top: small-sd-card-img-top | ||
| :class-body: small-sd-card | ||
| :class: small-sd-card | ||
| +++ | ||
| <a href="https://rocm.blogs.amd.com/artificial-intelligence/xgboost-multi-gpu/README.html" class="card-header-link"> | ||
| <h2 class="card-header">Accelerating XGBoost with Dask using multiple AMD GPUs</h2> | ||
| </a> | ||
| <p class="paragraph"> XGBoost is an optimized library for distributed gradient boosting. It has become the leading machine learning library for solving regression and classification problems.</p> | ||
| ::: | ||
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| # ROCm-Finance: ROCm toolkit for finance | ||
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| ROCm-Finance pulls the trajectory of tomorrow into today: an open toolkit on the [ROCm](https://rocm.docs.amd.com/) stack that | ||
| delivers GPU-native gradient-boosting stacks that the industry already trusts. XGBoost, | ||
| LightGBM, and ThunderGBM, tuned for [AMD Instinct](https://www.amd.com/en/products/accelerators/instinct.html) | ||
| accelerators, so training, scoring, and simulation work land closer to real time than the CPU-era | ||
| baselines could achieve. | ||
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| ROCm-Finance collapses the distance between signal and decision. The same workloads that once | ||
| queued overnight now run in minutes. Risk, fraud detection, forecasting, and simulation pipelines step | ||
| into the high-bandwidth GPU computing ROCm was built to serve. ROCm-Finance provides production-oriented kernels, memory paths, and scaling behavior so your boosting jobs feel like | ||
| they arrived from the next generation, even on this week's cluster. | ||
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| For more information on ROCm-Finance, including comparisons, prerequisites, installation, and deep API | ||
| reference, see the [ROCm-Finance documentation](https://rocm.docs.amd.com/projects/rocm-finance/en/latest/index.html). | ||
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| :::::{grid} 2 2 2 2 | ||
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| ::::{grid-item-card} | ||
| :padding: 1 | ||
| :img-top: ../images/finance-1.png | ||
| :class-img-top: small-sd-card-img-top | ||
| :class-body: small-sd-card | ||
| :class: small-sd-card | ||
| +++ | ||
| <a href=./xgboost.html class="card-header-link"> | ||
| <h2 class="card-header">XGBoost</h2> | ||
| </a> | ||
| <p class="paragraph"> General-purpose GPU gradient boosting. Start here for high-performance workloads for data-intensive applications. | ||
| </p> | ||
| :::: | ||
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| ::::{grid-item-card} | ||
| :padding: 1 | ||
| :img-top: ../images/finance-2.png | ||
| :class-img-top: small-sd-card-img-top | ||
| :class-body: small-sd-card | ||
| :class: small-sd-card | ||
| +++ | ||
| <a href=./lightgbm.html class="card-header-link"> | ||
| <h2 class="card-header">LightGBM</h2> | ||
| </a> | ||
| <p class="paragraph"> Leaf-wise training. Strong fit when sparsity abounds and dataset size drives the bottleneck. | ||
| </p> | ||
| :::: | ||
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| ::::{grid-item-card} | ||
| :padding: 1 | ||
| :img-top: ../images/finance-3.png | ||
| :class-img-top: small-sd-card-img-top | ||
| :class-body: small-sd-card | ||
| :class: small-sd-card | ||
| +++ | ||
| <a href=./thundergbm.html class="card-header-link"> | ||
| <h2 class="card-header">ThunderGBM</h2> | ||
| </a> | ||
| <p class="paragraph"> GPU-oriented boosting for highly parallel, GPU-intensive training and simulation-style runs on high-dimensional datasets. | ||
| </p> | ||
| :::: | ||
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| ::::{grid-item-card} | ||
| :padding: 1 | ||
| :img-top: ../images/finance-4.png | ||
| :class-img-top: small-sd-card-img-top | ||
| :class-body: small-sd-card | ||
| :class: small-sd-card | ||
| +++ | ||
| <a href="https://github.com/ROCm/ROCm-Finance" class="card-header-link"> | ||
| <h2 class="card-header">GitHub</h2> | ||
| </a> | ||
| <p class="paragraph"> Source for all ROCm-Finance libraries on GitHub. | ||
| </p> | ||
| :::: | ||
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| ::::{grid-item-card} | ||
| :padding: 1 | ||
| :img-top: ../images/finance-5.png | ||
| :class-img-top: small-sd-card-img-top | ||
| :class-body: small-sd-card | ||
| :class: small-sd-card | ||
| +++ | ||
| <a href="https://github.com/ROCm/rocm-finance/tree/release/26.01/examples" class="card-header-link"> | ||
| <h2 class="card-header">Examples</h2> | ||
| </a> | ||
| <p class="paragraph"> Runnable examples on GitHub to explore the code. | ||
| </p> | ||
| :::: | ||
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| ::::{grid-item-card} | ||
| :padding: 1 | ||
| :img-top: ../images/finance-6.png | ||
| :class-img-top: small-sd-card-img-top | ||
| :class-body: small-sd-card | ||
| :class: small-sd-card | ||
| +++ | ||
| <a href=./finance-blogs.html class="card-header-link"> | ||
| <h2 class="card-header">ROCm-Finance Blogs</h2> | ||
| </a> | ||
| <p class="paragraph"> Browse blogs detailing how to accelerate your finance workloads using gradient boosting on AMD Instinct GPUs. | ||
| </p> | ||
| :::: | ||
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| ::::: | ||
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| # LightGBM (ROCm-Finance) | ||
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| LightGBM is how ROCm-Finance answers scale: leaf-wise training that shines when dataset size—wide | ||
| feature stores, long histories, dense microstructure matrices—would otherwise push | ||
| decisions into the next shift. On Instinct, that wall between overnight queues and minutes | ||
| thins out; the same boosting idiom, routed through ROCm's high-bandwidth, multi-GPU environment. | ||
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| Reach for LightGBM when volume is the bottleneck, and you still want gradient boosting semantics | ||
| with GPU-native backing. | ||
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| ::::{grid} 2 2 2 2 | ||
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| :::{grid-item-card} | ||
| :padding: 1 | ||
| :img-top: ../images/finance-6.png | ||
| :class-img-top: small-sd-card-img-top | ||
| :class-body: small-sd-card | ||
| :class: small-sd-card | ||
| +++ | ||
| <a href="https://rocm.docs.amd.com/projects/lightgbm/en/latest/" class="card-header-link"> | ||
| <h2 class="card-header">Documentation</h2> | ||
| </a> | ||
| <p class="paragraph"> Installation instructions, how-to guides, and API reference material are available on the ROCm Documentation site. | ||
| </p> | ||
| ::: | ||
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| :::{grid-item-card} | ||
| :padding: 1 | ||
| :img-top: ../images/finance-2.png | ||
| :class-img-top: small-sd-card-img-top | ||
| :class-body: small-sd-card | ||
| :class: small-sd-card | ||
| +++ | ||
| <a href="https://github.com/ROCm/LightGBM/" class="card-header-link"> | ||
| <h2 class="card-header">Github</h2> | ||
| </a> | ||
| <p class="paragraph"> View the LightGBM source code on Github. | ||
| </p> | ||
| ::: | ||
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| :::: |
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| # ThunderGBM (ROCm-Finance) | ||
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| Use ThunderGBM when parallelism and raw throughput dominate the story: | ||
| massively parallel trees, simulation-scale batches, and scenario grids that want the accelerator | ||
| to do the heavy lifting today—not in some speculative later hardware generation. ThunderGBM collapses the | ||
| signal-to-decision distance, optimized for highly parallel, | ||
| GPU-intensive training runs on [AMD Instinct](https://www.amd.com/en/products/accelerators/instinct.html) silicon. | ||
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| ::::{grid} 2 2 2 2 | ||
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| :::{grid-item-card} | ||
| :padding: 1 | ||
| :img-top: ../images/finance-6.png | ||
| :class-img-top: small-sd-card-img-top | ||
| :class-body: small-sd-card | ||
| :class: small-sd-card | ||
| +++ | ||
| <a href="https://rocm.docs.amd.com/projects/thundergbm/en/latest/" class="card-header-link"> | ||
| <h2 class="card-header">Documentation</h2> | ||
| </a> | ||
| <p class="paragraph"> ThunderGBM on ROCm—component documentation is available on the ROCm Documentation site. | ||
| </p> | ||
| ::: | ||
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| :::{grid-item-card} | ||
| :padding: 1 | ||
| :img-top: ../images/finance-3.png | ||
| :class-img-top: small-sd-card-img-top | ||
| :class-body: small-sd-card | ||
| :class: small-sd-card | ||
| +++ | ||
| <a href="https://github.com/ROCm/ThunderGBM/" class="card-header-link"> | ||
| <h2 class="card-header">Github</h2> | ||
| </a> | ||
| <p class="paragraph"> View the ThunderGBM source code on Github. | ||
| </p> | ||
| ::: | ||
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| :::: |
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| # XGBoost (ROCm-Finance) | ||
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| XGBoost is the general-purpose engine in ROCm-Finance: tabular risk, fraud detection, pricing-side features, and trading-adjacent workloads. | ||
| Use it when you want a familiar level-wise boosting path with broad finance coverage and a | ||
| straightforward on-ramp from yesterday's pipelines to tomorrow's throughput. | ||
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| ::::{grid} 2 2 2 2 | ||
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| :::{grid-item-card} | ||
| :padding: 1 | ||
| :img-top: ../images/finance-6.png | ||
| :class-img-top: small-sd-card-img-top | ||
| :class-body: small-sd-card | ||
| :class: small-sd-card | ||
| +++ | ||
| <a href="https://rocm.docs.amd.com/projects/xgboost/en/latest/" class="card-header-link"> | ||
| <h2 class="card-header">Documentation</h2> | ||
| </a> | ||
| <p class="paragraph"> XGBoost on ROCm—installation, tuning, and API reference are available on the ROCm Documentation site. | ||
| </p> | ||
| ::: | ||
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| :::{grid-item-card} | ||
| :padding: 1 | ||
| :img-top: ../images/finance-1.png | ||
| :class-img-top: small-sd-card-img-top | ||
| :class-body: small-sd-card | ||
| :class: small-sd-card | ||
| +++ | ||
| <a href="https://github.com/ROCm/XGBoost/" class="card-header-link"> | ||
| <h2 class="card-header">Github</h2> | ||
| </a> | ||
| <p class="paragraph"> View the XGBoost source code on Github. | ||
| </p> | ||
| ::: | ||
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| :::: |
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