Field-programmable logic devices with optical input–output
Bibliographic record
Abstract
A field-programmable logic device (FPLD) with optical I/O is described. FPLD's with optical I/O can have their functionality specified in the field by means of downloading a control-bit stream and can be used in a wide range of applications, such as optical signal processing, optical image processing, and optical interconnects. Our device implements six state-of-the-art dynamically programmable logic arrays (PLA's) on a 2 mm x 2 mm die. The devices were fabricated through the Lucent Technologies-Advanced Research Projects Agency-Consortium for Optical and Optoelectronic Technologies in Computing (Lucent/ARPA/COOP) workshop by use of 0.5-microm complementary metal-oxide semiconductor-self-electro-optic device technology and were delivered in 1998. All devices are fully functional: The electronic data paths have been verified at 200 MHz, and optical tests are pending. The device has been programmed to implement a two-stage optical switching network with six 4 x 4 crossbar switches, which can realize more than 190 x 10(6) unique programmable input-output permutations. The same device scaled to a 2 cm x 2 cm substrate could support as many as 4000 optical I/O and 1 Tbit/s of optical I/O bandwidth and offer fully programmable digital functionality with approximately 110,000 programmable logic gates. The proposed optoelectronic FPLD is also ideally suited to realizing dense, statically reconfigurable crossbar switches. We describe an attractive application area for such devices: a rearrangeable three-stage optical switch for a wide-area-network backbone, switching 1000 traffic streams at the OC-48 data rate and supporting several terabits of traffic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".