Pipeline Indirection for Compressed Graph List Access
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Solution Overview
Problem
Current systems face performance overheads when accessing compressed sparse matrices in CSR format due to the need for multiple memory accesses and round-trip latencies in graph applications, which hinders efficient processing of indirect loads and stores.
Innovation Solution
A pipeline indirection system that combines multiple operations into a single instruction, allowing for remote address computation and eliminating round-trip latencies by using op-engines to compute and access data locations efficiently within a compressed graphic list.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple memory accesses are performed to access compressed sparse matrices in CSR format, then data can be retrieved from memory, but performance overhead increases due to multiple read operations and round-trip latencies
Solution Approach 1:
The patent combines multiple separate memory access operations into a single unified indirect load instruction. Instead of performing separate reads for neighbor index lookup and value retrieval, the system executes one instruction that handles the entire indirection sequence, reducing memory access overhead and improving processing throughput for graph applications
Solution Approach 2:
The system pre-loads neighbor index data into register files before execution, and uses pipeline stages to prepare address computation in advance. By performing preliminary actions such as pre-fetching index data and pre-computing addresses in pipeline stages, the system reduces the critical path latency for indirect memory accesses
2Adaptability or versatility
If indirect load and store operations are supported with multiple memory accesses, then data can be accessed through neighbor indices, but latency per operation increases
Solution Approach 1:
The patent segments the indirect access operation into distinct pipeline stages: neighbor index read, address computation, and data load/store. By dividing the operation into manageable segments that can be processed in parallel pipeline stages, the system maintains versatile indirect access capability while reducing the time each segment takes to complete
Solution Approach 2:
The system introduces intermediary register files and pipeline buffers between the neighbor index and final data access. These intermediaries hold pre-fetched index data and computed addresses, allowing the main execution pipeline to proceed without waiting for slow memory accesses, thereby reducing overall operation latency
3Ease of operation
If separate instructions are used for each memory access operation, then each operation can be executed independently, but code efficiency decreases
Solution Approach 1:
The patent merges multiple independent memory access operations into a single compound indirect load/store instruction. This unified instruction handles the entire sequence of neighbor index lookup, address computation, and data access in one operation, improving code efficiency by reducing instruction count and execution overhead while maintaining operational independence through internal pipeline processing
Data Source
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AI summary
Disclosed embodiments relate to systems and methods for performing instructions to access a compressed graphic list. In one example, a processor includes fetch and decode circuitry to fetch and decode the single instruction to access the compressed graphic list, and execution circuitry to execute the decoded single instruction to cause access to the compressed graphic list by: receiving, from a load store queue, at a first op-engine associated with a first data location, an indirection request, computing, via the first op-engine, a second data location associated with a second op-engine, computing, via the second op-engine, a third data location associated with a third op-engine responsive to the indirection request, and providing, via the third op-engine, a data response to the load store queue responsive to receiving data from the third data location.