A Comparison of Profiling Tools for FPGA-Based Embedded Systems
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
This paper presents an analysis and comparison of the profiled results using software-based profilers (SBP) and FPGA-based profilers (FPGA-BP) for a Nios II Processor system. SBP tools are commonly used to detect performance bottlenecks of a program by applying instrumentation code at the binary level and using sampling methods for performance data gathering. This can cause the reported profiled results to be inaccurate which can mislead the embedded designer to implement the improper software function in the hardware domain. FPGA-BP tools are profilers that contain dedicated hardware that can accurately measure the performance of the software system running on a soft-core processor. They require minimal code modification and do not use any sampling techniques to collect performance data. This can provide accurate results that embedded designers can use to create an efficient and effective hardware-software partition of an embedded system.
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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 | 0.001 | 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 | 0.000 |
| 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