Hardware Object Memory Fabric for Big Data Performance
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Solution Overview
Problem
Current commodity hardware and software solutions are inadequate for meeting the demands of Cloud Computing and Big Data environments due to the separation of processing, memory, and storage, leading to inefficiencies and limitations in performance and scalability.
Innovation Solution
The implementation of an object memory fabric with hardware-based processing nodes that utilize a stream application programming interface (API) to manage memory objects natively, allowing for efficient communication and access across nodes without traditional Input/Output instructions, and eliminating distinctions between memory and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If processing, memory, and storage are separated and managed separately by software, then system flexibility and modularity are improved, but performance efficiency and data access speed deteriorate
Solution Approach 1:
The patent merges processing, memory, and storage management into a unified hardware-based object memory fabric system. This integration eliminates the software management layers between these components, enabling direct hardware access to memory objects stored on remote nodes through the memory fabric network, thereby resolving the contradiction between system flexibility and performance efficiency
2Adaptability or versatility
If each node is separated from other nodes by a physical computer network managed by software, then system scalability is improved, but communication overhead and data transfer latency increase
Solution Approach 1:
The patent replaces the software-based network management mechanism with a hardware-based object memory fabric. This hardware fabric directly connects memory modules across nodes, enabling efficient data transfer through dedicated memory channels rather than through software-managed network stacks, thereby reducing communication overhead while maintaining scalability
3Ease of operation
If traditional Input/Output instructions are used for memory access, then compatibility with existing systems is improved, but access speed and memory reference efficiency deteriorate
Solution Approach 1:
The patent changes the fundamental parameter of memory access by introducing memory reference instructions that directly access memory objects in the object memory fabric, bypassing traditional Input/Output instructions. This enables direct memory-to-memory transfers and eliminates the software mediation layer, significantly improving access speed while maintaining compatibility through the stream API interface
Data Source
AI summary
Embodiments of the invention provide systems and methods for managing processing, memory, storage, network, and cloud computing to significantly improve the efficiency and performance of processing nodes. More specifically, embodiments of the present invention are directed to a hardware-based processing node of an object memory fabric. The processing node may include a memory module storing and managing one or more memory objects, the one or more memory objects each include at least a first memory and a second memory, wherein the first memory has a lower latency than the second memory, and wherein each memory object is created natively within the memory module, and each memory object is accessed using a single memory reference instruction without Input/Output (I/O) instructions, wherein a set of data is stored within the first memory of the memory module; wherein the memory module is configured to receive an indication of a subset of the set of data that is eligible to be transferred between the first memory and the second memory; and wherein the memory module dynamically determines which of the subset of data will be transferred to the second memory based on access patterns associated with the object memory fabric.