Gigabyte-scale alignment of biological sequences: A case study of IO bandwidth reconfiguration for FPGA acceleration
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
We expose the implementation challenges to sustaining acceleration speedups on FPGAs as the size of the data set to be processed scales. We examine the implementation of an FPGA platform for the processing of gigabyte scale biological sequences, and illustrate the significant design changes that must be made to achieve a successful implementation. In doing so, we demonstrate that conventional accelerator architecture design choices that focus on throughput speedup, in isolation of system level IO bandwidth feasibility, cannot sustain their throughput levels as the input data set scales. This is shown to be primarily due to currently unavailable high-bandwidth large-scale data storage and retrieval for FPGAs. As a solution to this problem, we propose a general FPGA based IO infrastructure to utilize high bandwidth hard-drive storage options, as means to achieving sustained throughput in the face of large data.
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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 | 0.000 | 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 | 0.000 | 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