(When) will FPGAs kill ASICs? (panel session)
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
There was a time - in the dim historical past - when foundries actually made ASICs with only 5000 to 50,000 logic gates. But FPGAs and CPLDs conquered those markets and pushed ASIC silicon toward opportunities with more logic, volume, and speed. Today's largest FPGAs approach the few-million-gate size of a typical ASIC design, and continue to sprout embedded cores, such as CPUs, memories, and interfaces. And given the risks of nonworking nanometer silicon, FPGA costs and time-to-market are looking awfully attractive. So, will FPGAs kill ASICs? ASIC technologists certainly think not. ASICs are themselves sprouting patches of programmable FPGA fabric, and pushing new realms of size and especially speed. New tools claim to have tamed the convergence problems of older ASIC flows. Is the future to be found in a market full of FPGAs with ASIC-like cores? ASICs with FPGA cores? Other exotic hybrids? Our panelists will share their disagreements on these prognostications.
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 | 0.000 | 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 | 0.001 |
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