Stream-Aware Intelligent Memory Controller through HW/SW Co-Design
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
Memory hierarchy often represents a significant performance bottleneck in modern computing systems. A promising direction to mitigate this bottleneck is through HW/SW coordination at the system level. However, many existing solutions require changes to legacy programming paradigms, such as ISA extensions, and often provide specialized optimizations limited to specific modules or policies within the memory hierarchy. In this work, we introduce InterStellar, a HW/SW co-design methodology that overcomes these limitations. InterStellar enables the design of a stream-aware memory controller that dynamically adapts its scheduling and memory management policies while proactively batching future stream accesses from off-chip memory. The design is optimized not only for performance, but also for energy efficiency and bandwidth utilization. On systems with eight RISC-V cores, InterStellar achieves significant end-to-end speedup compared to a commercial off-the-shelf (COTS) memory controller: up to 2.72 × for PolyBench, 1.84 × for HPCG, 1.24 × for Rodinia, 1.47 × for Parboil, and 1.29 × for the Phoenix suite.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.006 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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