CXL-Interference: Analysis and Characterization in Modern Computer Systems (2411.18308v1)

Abstract: Compute Express Link (CXL) is a promising technology that addresses memory and storage challenges. Despite its advantages, CXL faces performance threats from external interference when co-existing with current memory and storage systems. This interference is under-explored in existing research. To address this, we develop CXL-Interplay, systematically characterizing and analyzing interference from memory and storage systems. To the best of our knowledge, we are the first to characterize CXL interference on real CXL hardware. We also provide reverse-reasoning analysis with performance counters and kernel functions. In the end, we propose and evaluate mitigating solutions.

• The paper introduces CXL-Interplay, showcasing up to a 93.2% bandwidth reduction in main memory from CXL non-temporal store operations.
• Microbenchmark tests and performance counters indicate that CXL traffic congests the CPU’s request table, increasing latency for memory-intensive operations.
• Software interventions like CPU restrictions and Memory Bandwidth Allocation effectively mitigate interference, improving performance in applications like RocksDB and Redis.

Analysis and Implications of CXL-Interference in Modern Computer Systems

The paper titled "CXL-Interference: Analysis and Characterization in Modern Computer Systems" provides a detailed exploration of the interference issues that arise when Compute Express Link (CXL) coexists with current memory and storage systems. CXL is an emerging interconnect technology designed to enhance data-centric applications by enabling high-speed, low-latency communication between processing and memory resources. Despite its advantages, the paper identifies potential interference challenges, which remain underexplored in existing research.

The paper introduces CXL-Interplay, a novel framework designed to systematically characterize and analyze the interference of CXL with traditional memory and storage systems. Through a series of microbenchmarks and evaluations on real CXL hardware, the authors document significant interference effects when CXL concurrently operates with main memory (MMEM) and storage systems, such as solid-state drives (SSD).

Key Findings

1. Microbenchmark Characterization:
   • The paper confirms substantial performance degradation of MMEM and SSD bandwidth, primarily due to CXL non-temporal store (ntst) operations. For instance, MMEM can experience up to a 93.2% decrease in bandwidth due to CXL interference.
   • It was found that the interference is less severe for CXL load and store operations, compared to ntst, particularly when interacting with SSDs.
2. Reverse-Reasoning Analysis:
   • Performance counter evaluations reveal that CXL traffic, especially ntst, significantly occupies the Table of Requests (TOR) inside the CPU, leading to TOR congestion and increased latency for other memory accesses.
   • The kernel-level analysis indicates that CXL interference increases the execution time of memory-intensive functions like memmove.
3. Real Application Evaluation:
   • The interference's impact extends to real-world applications such as RocksDB and Redis, where performance deterioration is observed under CXL traffic. However, the paper includes cases where CXL load operations, contrary to causing degradation, improve certain SSD applications' performance by reducing instruction counts.
4. Interference Mitigation:
   • The paper proposes and evaluates various software-based interventions, such as CPU usage restriction and frequency scaling. These interventions demonstrate significant recovery of MMEM performance at the cost of CXL throughput.
   • Memory Bandwidth Allocation (MBA) is highlighted as a promising strategy to mitigate interference without broadly impacting computational instructions.

Implications and Future Directions

The research has significant implications for the design and operation of data centers and server environments adopting CXL. Understanding and mitigating interference can lead to improved performance and reliability of these systems.

Theoretically, this paper highlights the importance of considering interference in system design and suggests that a comprehensive understanding of the interaction between CXL and existing memory technologies is crucial. Additionally, the proposed CXL-Interplay framework serves as a foundation for further research, enabling other researchers to investigate and develop hardware-level solutions to reduce or eliminate CXL-related interference.

Future research could explore more target-specific hardware solutions for dynamic regulation of CXL devices, possibly focusing on novel architectural designs that incorporate intelligent hardware schedulers. Furthermore, the findings suggest an opportunity to refine existing simulation tools to incorporate interference factors observed in real-world environments.

In conclusion, this paper provides a valuable contribution to understanding and characterizing CXL interference, offering practical strategies and insights that will inform the development of more robust CXL-integrated systems. These developments will be crucial as the industry continues to adopt and integrate CXL technology into diverse computing environments.