Fast critical sections via thread scheduling for FPGA-based multithreaded processors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As FPGA based systems including soft processors become increasingly common, we are motivated to better understand the architectural trade-offs and improve the efficiency of these systems. Previous work has demonstrated that support for multithreading in soft processors can tolerate pipeline and I/O latencies as well as improve overall system throughput-however earlier work assumes an abundance of completely independent threads to execute. In this work we show that for real workloads, in particular packet processing applications, there is a large fraction of processor cycles wasted while awaiting the synchronization of shared data structures, limiting the benefits of a multithreaded design. We address this challenge by proposing a method of scheduling threads in hardware that allows the multithreaded pipeline to be more fully utilized without significant costs in area or frequency. We evaluate our technique relative to conventional multithreading using both simulation and a real implementation on a NetFPGA board, evaluating three deep-packet inspection applications that are threaded, synchronize, and share data structures, and show that overall packet throughput can be increased by 63%, 31%, and 41% for our three applications.
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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