Toward a Software Infrastructure for the Cyclops-64 Cellular Architecture
Bibliographic record
Abstract
This paper presents the initial design of the Cyclops-64 (C64) system software infrastructure and tools under development as a joint effort between IBM T.J. Watson Research Center, ETI Inc. and the University of Delaware. The C64 system is the latest version of the Cyclops cellular architecture that consists of a large number of compute nodes each employs a multiprocessor-on-a-chip architecture with 160 hardware thread units. The first version of the C64 system software has been developed and is now under evaluation. The current version of the C64 software infrastructure includes a C64 toolchain (compiler, linker, functionally accurate simulator, runtime thread library, etc.) and other tools for system control (system initialization, diagnostics and recovery, job scheduler, program launching, etc.) This paper focuses on the following aspects of the C64 system software: (1) the C64 software toolchain; (2) the C64 Thread Virtual Machine (C64 TVM) with emphasis on TiNy ThreadsTM, the implementation of the C64 TVM; (3) the system software for host control. In addition, we illustrate, through two case studies, what an application developer can expect from the C64 architecture as well as some advantages of this architecture, in particular, how it provides a cost-effective solution. A C64 chip’s performance varies across different applications from 5 to 35 times faster than common off-the-self microprocessors.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".