An efficient instruction cache scheme for object-oriented languages
Bibliographic record
Abstract
We present an efficient cache scheme, which can considerably reduce instruction cache misses caused by procedure call/returns. This scheme employs N-way banks and XOR mapping functions. The main function of this scheme is to place a group of instructions separated by a call instruction into a bank according to the initial and final bank selection mechanisms. After the initial bank selection mechanism selects a bank on an instruction cache miss, the final bank selection mechanism will determine the final bank for updating a cache line as a correction mechanism. These two mechanisms can guarantee that recent groups of instructions exist in each bank safely. We have developed a simulation program by using Shade and Spixtools, provided by SUN Microsystems, on an ultra SPARC/10 processor. Our experimental results show that these schemes reduce conflict misses more effectively than skewed-associative caches in both C (up to 9.29% improvement) and C++ (up to 30.71% improvement) programs on L1 caches. In addition, they also allow for a significant miss reduction on Branch Target Buffers (BTB).
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".