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https://issues.apache.org/jira/browse/MAHOUT-878?focusedWorklogId=1001274&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-1001274
]
ASF GitHub Bot logged work on MAHOUT-878:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 22/Jan/26 06:39
Start Date: 22/Jan/26 06:39
Worklog Time Spent: 10m
Work Description: rich7420 commented on code in PR #881:
URL: https://github.com/apache/mahout/pull/881#discussion_r2715514875
##########
qdp/qdp-core/src/lib.rs:
##########
@@ -300,6 +300,269 @@ impl QdpEngine {
encoding_method,
)
}
+
+ /// Encode from existing GPU pointer (zero-copy for CUDA tensors)
+ ///
+ /// This method enables zero-copy encoding from PyTorch CUDA tensors by
accepting
+ /// a raw GPU pointer directly, avoiding the GPU→CPU→GPU copy that would
otherwise
+ /// be required.
+ ///
+ /// TODO: Refactor to use QuantumEncoder trait (add `encode_from_gpu_ptr`
to trait)
+ /// to reduce duplication with AmplitudeEncoder::encode(). This would also
make it
+ /// easier to add GPU pointer support for other encoders (angle, basis) in
the future.
+ ///
+ /// # Arguments
+ /// * `input_d` - Device pointer to input data (f64 array on GPU)
+ /// * `input_len` - Number of f64 elements in the input
+ /// * `num_qubits` - Number of qubits for encoding
+ /// * `encoding_method` - Strategy (currently only "amplitude" supported)
+ ///
+ /// # Returns
+ /// DLPack pointer for zero-copy PyTorch integration
+ ///
+ /// # Safety
+ /// The input pointer must:
+ /// - Point to valid GPU memory on the same device as the engine
+ /// - Contain at least `input_len` f64 elements
+ /// - Remain valid for the duration of this call
+ #[cfg(target_os = "linux")]
+ pub unsafe fn encode_from_gpu_ptr(
Review Comment:
no problem!
Issue Time Tracking
-------------------
Worklog Id: (was: 1001274)
Time Spent: 5.5h (was: 5h 20m)
> Provide better examples for the parallel ALS recommender code
> -------------------------------------------------------------
>
> Key: MAHOUT-878
> URL: https://issues.apache.org/jira/browse/MAHOUT-878
> Project: Mahout
> Issue Type: Task
> Affects Versions: 1.0.0
> Reporter: Sebastian Schelter
> Assignee: Sebastian Schelter
> Priority: Major
> Fix For: 0.6
>
> Attachments: MAHOUT-878.patch
>
> Time Spent: 5.5h
> Remaining Estimate: 0h
>
> We should provide examples that show how to apply the parallel ALS
> recommender to the Netflix or KDD2011 datasets.
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