Designing a configurable IEEE-compliant FPU that supports variable precision for soft 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
FPGAs are an increasingly popular medium for many high-performance data center workloads and the rapidly-expanding artificial intelligence domain. These applications often make extensive use of floating-point (FP) numbers defined by the IEEE 754 standard [1]. Although researchers have extensively studied FPGA-based hardware FP implementations, existing work has largely focused on standalone and throughput-optimized data-path designs. Such designs optimize performance by increasing throughput with long pipelines and high frequencies. This approach is not suitable for soft processors, which are more sensitive to latency in order to reduce stalls due to data hazards. Additionally, the frequency ceiling imposed by other internal components of the soft processor necessarily limits the maximum operating frequency of the Floating-Point Unit (FPU).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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