Retrospective Study of Performance and Power Consumption of Computer Systems
Bibliographic record
Abstract
Power consumption has become an important factor in the design of high-performance computer systems. The power consumption of newer systems is now published but is unknown for many older systems. Data for only two or three generations of systems are insufficient for projecting the performance/power of future systems. We measured the performance and power consumption of 70 computer systems from 1989 to 2011. Our collection of computers included desktop and laptop personal computers, workstations, handheld devices and supercomputers. This is the first paper reporting the performance and power consumption of systems over twenty years, using a uniform method. The primary benchmark we used was Dhrystone. We also used NAS Parallel Benchmarks and CPU2006 suite. The Dhrystone/power ratio was found to be growing exponentially. The data we obtained indicates that the Dhrystone result and the CINT2006 in SPEC CPU2006 correlate closely. The NAS Parallel Benchmarks and CFP2006 results also correlate. Using the trend of Dhrystone/power that we obtained, we predict that the Dhrystone/power ratio will reach 2, 963 VAX MIPS/Watt in 2018, when exaflops machines are expected to appear.
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.
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".