MPSoC memory optimization using program transformation
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
Multiprocessor system-on-a-chip (MPSoC) architectures have received a lot of attention in the past years, but few advances in compilation techniques target these architectures. This is particularly true for the exploitation of data locality. Most of the compilation techniques for parallel architectures discussed in the literature are based on a single loop nest. This article presents new techniques that consist in applying loop fusion and tiling to several loop nests and to parallelize the resulting code across different processors. These two techniques reduce the number of memory accesses. However, they increase dependencies and thereby reduce the exploitable parallelism in the code. This article tries to address this contradiction. To optimize the memory space used by temporary arrays, smaller buffers are used as a replacement. Different strategies are studied to optimize the processing time spent accessing these buffers. The experiments show that these techniques yield a significant reduction in the number of data cache misses (30%) and in processing time (50%).
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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