A Streaming Accelerator for Heterogeneous CPU-FPGA Processing of Graph Applications
Why this work is in the frame
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Bibliographic record
Abstract
We explore the heterogeneous acceleration of graph processing on a platform that tightly integrates an FPGA with a multicore CPU to share system memory in a cache-coherent manner. We design an accelerator for the scatter phase of scatter-gather vertex-centric iterative graph processing. The accelerator accesses graph data exclusively from system memory, sharing it at the cache line granularity with the CPU, thus enabling the concurrent use of both the accelerator and software threads. We implement and evaluate the accelerator on the second generation Intel Heterogeneous Architecture Research Platform (HARPv2). Our evaluation, using two key graph processing kernels and both synthetically-generated and real-world graphs, shows that: (1) our accelerator delivers a performance improvement of about 2.4X over a single CPU thread, (2) our concurrent use of software and hardware is efficient and delivers speedups over the use of just software threads or just the accelerator, and (3) heterogeneous hardware-software acceleration delivers high graph processing throughputs. These results demonstrate the viability and promise of combined CPU-FPGA processing in contrast to the traditional offload model that leaves the CPU idle during acceleration.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it