Parallel Radix Sort on the AMD Fusion Accelerated Processing Unit
Bibliographic record
Abstract
We design, implement and evaluate a parallel radix sort that simultaneously utilizes the CPU and GPU devices on the AMD Fusion APU. The parallel sort, referred to as Fusion Sort, partitions the sort keys between the CPU and GPU devices and utilizes the integrated memory system of the APU to avoid data copying between the devices. We identify three design issues that impact overhead and performance: the granularity of sharing between the two devices, the scheme of data partitioning and the allocation of data in memory regions accessible by each device. We present three variants of Fusion Sort that share data at coarse and fine granularities and with fixed and variable data partitioning schemes. In each variant, data is allocated to minimize the overhead of non-preferred memory accesses of each device. Our evaluation shows that fine-grain sharing with variable data partitioning performs the best. Further, Fusion Sort outperforms CPU-only and GPU-only parallel radix sorts by up to 1.8X and 1.9X respectively. These results demonstrate the viability of the integrated memory system of the APU in the context of sorting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".