Challenges of Memory Management on Modern NUMA System
Why this work is in the frame
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Bibliographic record
Abstract
Modern server-class systems are typically built as several multicore chips put together in a single system. Each chip has a local DRAM (dynamic random-access memory) module; together they are referred to as a node. Nodes are connected via a high-speed interconnect, and the system is fully coherent. This means that, transparently to the programmer, a core can issue requests to its node’s local memory as well as to the memories of other nodes. The key distinction is that remote requests will take longer, because they are subject to longer wire delays and may have to jump several hops as they traverse the interconnect. The latency of memory-access times is hence non-uniform, because it depends on where the request originates and where it is destined to go. Such systems are referred to as NUMA (non-uniform memory access).
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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 | 0.000 |
| 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