Parallel Processing Elements for Mass Spectrometry Database Search
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Solution Overview
Problem
Mass-spectrometry-based analysis faces significant computation and communication bottlenecks due to high-resolution data processing, particularly in database search algorithms like SEQUEST and X!Tandem, which lead to increased computation load and inefficient memory access.
Innovation Solution
A novel system architecture utilizing parallel processing elements (PEs) with adaptive caching and first-come first-serve (FCFS) bus arbitration, coupled with on-chip RAM and a PCIe DMA bridge, minimizes communication overhead and synchronizes memory access, allowing for efficient computation of cross-correlation scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If database search algorithms (SEQUEST, X!Tandem, MSFragger) are used to search high resolution mass-spectrometry data against peptide databases, then identification quality is improved, but computation load increases significantly
Solution Approach 1:
The system divides the computation into multiple independent tasks by assigning different peptide database segments to different processing elements (PEs). Each PE handles a specific portion of the peptide database simultaneously, enabling parallel processing that maintains identification quality while reducing total computation time.
Solution Approach 2:
The patent introduces a new computational dimension by implementing asynchronous parallel processing across multiple PEs. Instead of sequential processing, the system executes database search algorithms simultaneously across multiple threads, transforming the computation from one-dimensional (sequential) to multi-dimensional (parallel/asynchronous) execution.
2Productivity
If parallel processing elements are used to reduce computation time, then productivity is improved, but communication overhead and memory access inefficiency increase
Solution Approach 1:
Each processing element is equipped with its own local memory (on-chip RAM) that stores frequently accessed peptide database segments. This local memory approach reduces the need for PEs to communicate through the shared bus for every data access, thereby reducing communication overhead while maintaining high computational throughput.
Solution Approach 2:
The patent introduces an intermediary memory hierarchy with on-chip RAM for each PE and shared memory for storing peptide databases and mass spectrometry data. This intermediary memory structure mediates between the PEs and external memory, reducing direct bus traffic and communication overhead while enabling efficient data access.
3Device complexity
If multiple PEs share a common memory bus, then device complexity is reduced, but memory access efficiency deteriorates due to arbitration delays
Solution Approach 1:
The system implements dynamic memory access patterns where PEs asynchronously retrieve peptide database segments from shared memory based on their current processing needs. The memory bus arbitration uses a first-come-first-serve mechanism that dynamically allocates access rights, allowing efficient memory retrieval without requiring complex synchronized protocols.
Data Source
AI summary
Systems, architectures, devices, and methods for matching experimentally acquired mass spectrometry data with a peptide database are provided. The system architecture can include a host central processing unit (CPU) system, a bridge connecting the CPU system with a core control register (or registers), a plurality of processing elements (PEs), and a bus arbiter. The PEs can execute the computations in a parallel and asynchronous manner. The bus arbiter can be a first-come first-serve (FCFS)-based bus arbiter (i.e., can utilize an FCFS-based arbitration scheme).