SDXI Smart Data Accelerator Pipelining Offload Operations
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Solution Overview
Problem
Current information handling systems face inefficiencies in processing and transferring data due to the need for processor intervention in data exchanges, especially when using Direct Memory Access (DMA) hardware, which can lead to processing overhead and resource utilization issues.
Innovation Solution
The implementation of a Smart Data Accelerator Interface (SDXI) architecture that incorporates multiple processing elements and accelerators, enabling pipelining, compounding, and chaining of data transfer and offload operations through standardized SDXI commands and descriptors, reducing the reliance on host processing system resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If processor intervention is used in data exchanges with DMA hardware, then data transfer reliability is improved, but processing overhead and resource utilization deteriorate
Solution Approach 1:
The patent segments data transfer operations into multiple independent stages (data movement, data processing, and completion notification) that can be executed independently by different hardware components. The processor only needs to initiate operations and receive final completion signals, while intermediate operations are handled by dedicated hardware engines, reducing processor intervention overhead while maintaining reliability through structured operation breakdown.
Solution Approach 2:
The patent introduces completion signals as intermediary mechanisms that coordinate between hardware engines and the processor. These signals act as mediators that allow hardware components to communicate operation status without requiring continuous processor intervention, enabling asynchronous operation and reducing processor overhead while ensuring data transfer reliability through proper synchronization.
2Manufacturing precision
If multiple data transfer operations are performed sequentially with processor intervention, then operation accuracy is improved, but productivity deteriorates
Solution Approach 1:
The patent enables continuous data transfer operations by allowing multiple data movement and processing operations to be initiated in sequence without waiting for processor intervention between each operation. Hardware engines execute operations continuously based on predefined descriptors, with the processor only needing to queue operations and receive final completion signals, thereby maintaining operation accuracy while significantly improving throughput through uninterrupted processing.
Solution Approach 2:
The patent uses descriptors to pre-configure data transfer operations with all necessary parameters (source, destination, processing rules) before execution. This preliminary configuration allows hardware engines to execute multiple operations autonomously without requiring processor intervention during execution, ensuring operation accuracy through pre-validated parameters while improving productivity through autonomous continuous operation.
3Measurement precision
If host processing system resources are heavily utilized for data management, then control precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts data management functions (data movement, processing, and status notification) from the host processing system and implements them in dedicated hardware engines within the information handling device. This extraction reduces host processing system resource utilization by offloading routine operations to autonomous hardware, while control precision is maintained through standardized completion signal protocols that ensure accurate operation tracking and synchronization.
Data Source
AI summary
An information handling system includes a processor and a hardware device. The hardware device includes a first engine to provide a first operation on data, and a second engine to provide a second operation on data. The processor provides a command to the hardware device. The command directs the first engine to perform the first operation on first data to create second data based upon the performance of the first operation on the first data, and directs the second engine to perform the second operation on the second data to create third data based upon the performance of the second operation on the second data in response to a completion signal. The hardware device is configured to provide the completion signal to the second engine when the performance of the first operation on the first data is completed.


