Name
Abstract | ||
|---|---|---|
Declarative memory enables cognitive agents to effectively store and retrieve factual memory in real-time. Increasing the capacity of a real-time agent's declarative memory increases an agent's ability to interact intelligently with its environment but requires a scalable retrieval system. This work represents an extension of the Accelerated Declarative Memory (ADM) system, referred to as Hardware Accelerated Declarative Memory (HADM), to execute retrievals on a GPU. HADM also presents improvements over ADM's CPU execution and considers critical behavior for indefinitely running declarative memories. The negative effects of a constant maximum associative strength are considered, and mitigating solutions are proposed. HADM utilizes a GPU to process the entire semantic network in parallel during retrievals, yielding significantly faster declarative retrievals. The resulting GPU-accelerated retrievals show an average speedup of approximately 70 times over the previous Service Oriented Architecture Declarative Memory (soaDM) implementation and an average speedup of approximately 5 times over ADM. HADM is the first GPU-accelerated declarative memory system in existence. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TPDS.2018.2866848 | IEEE Transactions on Parallel and Distributed Systems |
Keywords | Field | DocType |
Computer architecture,Graphics processing units,Acceleration,Hardware,Semantics,Real-time systems,Toy manufacturing industry | Associative property,CUDA,Computer science,Semantic network,Cognition,Computer hardware,Semantics,Service-oriented architecture,Speedup,Scalability | Journal |
Volume | Issue | ISSN |
30 | 3 | 1045-9219 |
Citations | PageRank | References |
1 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mark Edmonds | 1 | 7 | 2.70 |
| Tanvir Atahary | 2 | 4 | 2.50 |
| Scott Douglass | 3 | 4 | 2.50 |
| Tarek M. Taha | 4 | 280 | 32.89 |