Acceleration of the Secure Hash Algorithm-256 (SHA-256) on an FPGA-CPU Cluster Using OpenCL
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Bibliographic record
Abstract
The Secure Hash Algorithm-256 (SHA-256) is a cryptographic function used in a wide variety of applications ranging from Internet of Things micro-devices to highperformance systems. This paper studies a set of implementations of the SHA-256 on a field-programmable gate array (FPGA) elaborated using the Open Computing Language (OpenCL). These implementations apply several optimization techniques to improve their respective throughputs. Reported results show that a combination of OpenCL optimization techniques allows obtaining an implementation offering a 90x speed-up when compared to an unoptimized OpenCL implementation. Moreover, the best reported optimized implementation achieves a throughput of 3973 Mbps, which is 4.3 times higher than the best previously published HLS-based SHA-256 implementation and even higher than the previously published implementations using a hardware description language. To our knowledge, this work is the first that proposes an OpenCL-based FPGA implementation of SHA-256 and its OpenCL-based optimization 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.000 |
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