Distributed Computing Nodes with Integrated Circuit Dice
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Solution Overview
Problem
The von Neumann bottleneck, which arises from the separation of processors and memory in modern computer architectures, limits processing speed due to lower data bus throughput compared to processor speed, and this issue is exacerbated in distributed computing environments where multiple processors experience compounded delays.
Innovation Solution
The implementation of a distributed computing system with integrated circuit dice arranged in layers, where each die has multiple connection pads for direct communication, and a connector system that allows for dynamic reconfiguration and efficient data transfer between adjacent dice, enabling parallel and serial connections to optimize data access and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Weight of moving object
If processors and memory are separated on a motherboard with a data bus connection, then the computer can follow the von Neumann architecture with independent processing and storage units, but the data bus throughput becomes lower than processor speed, creating a performance bottleneck
Solution Approach 1:
The system divides the distributed computing system into multiple computing nodes, each with its own processor and memory. This segmentation allows parallel processing across nodes while maintaining the von Neumann architecture benefits of separation, thereby improving overall productivity without sacrificing the processing-memory separation advantage.
Solution Approach 2:
The patent transitions from a single-processor von Neumann bottleneck to a multi-dimensional distributed system where multiple processors operate in parallel across different nodes. This dimensional expansion from 1D (single processor) to 2D/3D (multiple nodes in a distributed network) resolves the throughput limitation by providing multiple concurrent data access paths.
2Productivity
If multiple processors are used in a distributed computing environment, then processing capacity increases, but delays on each motherboard's data bus are compounded, worsening overall system performance
Solution Approach 1:
The system performs preliminary routing and data preparation at each computing node before data transmission is needed. By pre-positioning data and instructions at the appropriate nodes and establishing communication paths in advance, the system reduces actual transmission delays and prevents compounding bottlenecks in the distributed environment.
Solution Approach 2:
The patent introduces intermediary components including local caches, buffer memory, and routing logic at each computing node. These intermediaries decouple the direct data bus dependency between processors and memory, allowing asynchronous operation and reducing the compounding effect of data bus delays across multiple processors.
3Speed
If processor speed and memory size increase at faster rates than data bus throughput improvements, then computing power and storage capacity improve, but the von Neumann bottleneck becomes more severe
Solution Approach 1:
The patent merges multiple computing nodes into a unified distributed system where processors can access both local and remote memory resources. This merging creates aggregate bandwidth that scales with the number of nodes, allowing effective processing speed to keep pace with individual processor speed improvements by providing parallel data access paths.
Solution Approach 2:
Each computing node in the distributed system is designed with universal functionality, including local processing units, memory, and communication interfaces. This multi-functionality allows any node to serve multiple roles (processing, storage, routing), thereby optimizing resource utilization and maintaining high effective processing speed across the entire system as individual components scale.
Data Source
AI summary
On a typical motherboard the processor and memory are separated by a printed circuit data bus that traverses the motherboard. Throughput, or data transfer rate, on the data bus is much lower than the rate at which a modern processor can operate. The difference between the data bus throughput and the processor speed significantly limits the effective processing speed of the computer when the processor is required to process large amounts of data stored in the memory. The processor is forced to wait for data to be transferred to or from the memory, leaving the processor under-utilized. The delays are compounded in a distributed computing system including a number of computers operating in parallel. The present disclosure describes systems, method and apparatus that tend to alleviate delays so that memory access bottlenecks are not compounded within distributed computing systems.