Ariel; A scalable multiprocessor for the simulation of neural networks

Journal Article · Thu Mar 01 04:00:00 EST 1990 · Computer Architecture News; (USA)

DOI:https://doi.org/10.1145/379126.379138· OSTI ID:7052290

Frazier, G ^[1]

---

1. Texas Instruments, Inc., Dallas, TX (USA)

{ital Ariel} is a multiprocessor architecture developed to stimulate neural networks and other models of distributed computation. The design is based upon a hierarchical network of coarse-grained processing modules. The module hardware uses fast digital signal processors and very large semiconductor memories to provide the throughput and storage capacity required to simulate large networks. The objective is to provide a system that can be scaled up to simulate neural networks composed of millions of nodes and 10s of billions of interconnections at rates exceeding 100 billion connection operations per second. This paper discusses the technical challenges in neural network simulation and describes {ital Ariel's} major components.

• OSTI ID: 7052290
• Journal Information: Computer Architecture News; (USA), Journal Name: Computer Architecture News; (USA) Vol. 18:1; ISSN CANED; ISSN 0163-5964
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
990200* -- Mathematics & Computers
ARRAY PROCESSORS
COMPUTER ARCHITECTURE
COMPUTER CODES
COMPUTER NETWORKS
COMPUTERIZED SIMULATION
DATA PROCESSING
DIGITAL SYSTEMS
DISTRIBUTED DATA PROCESSING
MEMORY DEVICES
NEURAL NETWORKS
PARALLEL PROCESSING
PROCESSING
PROGRAMMING
SEMICONDUCTOR DEVICES
SIMULATION
TECHNOLOGY ASSESSMENT