A High Performance DDR4 Memory Controller on FPGA
Bibliographic record
Abstract
We introduce a high-performance DDR4 SDRAM memory controller synthesizable design for AMD/Xilinx's FPGA devices. Due to limitations in operating frequency, the design on FPGA presents additional challenges compared to ASIC: in particular, the controller must be able to issue 4 DRAM commands in a single clock cycle. Utilizing Xilinx's memory controller (MIG) as a foundational framework, our design incorporates features such as the discrimination of received requests based on their origin and the implementation of the FR-FCFS arbitration scheme in the front-end scheduler. Additionally, our memory controller utilizes the Round Robin arbitration scheme in the back-end scheduler to optimize throughput through effective bank parallelism. Our memory controller is able to perform DRAM initialization, refresh, and calibration. Its design is extensible, allowing for further development of other types of DDR4 memory controllers and adaptation for various DDR4 speed grades. To evaluate the performance of our memory controller and Xilinx's MIG, we conducted extensive assessments using both realistic and synthetic traces in simulation. The obtained results provide a comprehensive comparison of their performance across various scenarios, offering valuable insights for further developments in the field.
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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 | 0.001 | 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 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".