TAIGA: A new RISC-V soft-processor framework enabling high performance CPU architectural features
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
Recently, there has been an increased focus on integration of reconfigurable fabric with modern processors. However, existing soft-processors are optimized to leverage older FPGA fabrics, focus primarily on resource minimization and have fixed-pipeline designs that limit the scope for tightly integrated hardware accelerators. In this work, we present Taiga: a RISC-V, 32-bit, soft-processor architecture supporting the RISC-V Multiply/Divide and Atomic operations extensions (RV32IMA) designed to support Linux-based shared-memory systems. The processor design is highly configurable and features a standardized interface for functional units allowing for ease of integration of new functional units. Despite a more complex pipeline, our design uses approximately 33% fewer slices while clocking 39% faster than a LEON3 based system built on a Xilinx Zynq X7CZ020.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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