Automated Synthesis of Streaming Transfer Level Hardware Designs
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 modern field-programmable gate arrays (FPGA) enable high computing performance and efficiency, their programming with low-level hardware description languages is time-consuming and remains a major obstacle to their adoption. High-level synthesis compilers are able to produce register-transfer-level (RTL) designs from C/C++ algorithmic descriptions, but despite allowing significant design-time improvements, these tools are not always able to generate hardware designs that compare to handmade RTL designs. In this article, we consider synthesis from an intermediate-level (IL) language that allows the description of algorithmic state machines handling connections between streaming sources and sinks. However, the interconnection of streaming sources and sinks can lead to cyclic combinational relations, resulting in undesirable behaviors or un-synthesizable designs. We propose a functional-level methodology to automate the resolution of such cyclic relations into acyclic combinational functions. The proposed IL synthesis methodology has been applied to the design of pipelined floating-point cores. The results obtained show how the proposed IL methodology can simplify the description of pipelined architectures while enabling performances that are close to those achievable through an RTL design methodology.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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