Search arXivSearch

arXiv · 2607.24849

Enhancing Error Detection Performance through Parallel CRC Computation on Multi-Core Architectures

Abstract

Cyclic Redundancy Check (CRC) remains one of the most widely used error-detection mechanisms in communication, storage, and embedded systems. However, conventional software CRC implementations suffer from inherent sequential dependencies that limit efficient utilization of modern multi-core processors. This paper presents a generalized software-based parallel CRC framework for multi-core architectures using POSIX threads. The proposed framework supports multiple CRC variants, including CRC-8, CRC-16, CRC-32, CRC-64, and CRC-128, within a unified implementation model. To preserve correctness during parallel execution, the framework employs a GF(2)-based CRC combination mechanism rather than naive XOR aggregation. The combine stage is formulated using polynomial arithmetic and matrix-based shifting operations over GF(2), ensuring equivalence between parallel and serial CRC computation. The proposed method was evaluated using multiple workload sizes and thread configurations. Experimental analysis includes execution time, throughput, latency, scalability behavior, and energy estimation under varying thread counts. Results indicate that parallel execution significantly improves performance for large datasets, achieving approximately 3-4x speedup on the evaluated platform while preserving exact CRC correctness. Comparative discussion with representative CRC optimization approaches, including lookup-table methods, slicing-by-8, SIMD/vectorized CRC, and hardware-assisted CRC techniques, is also provided to position the proposed framework within the broader CRC optimization landscape. Overall, the proposed approach provides a portable and generalized software framework for correctness-preserving parallel CRC acceleration on general-purpose multi-core systems.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Mohammad Javad Khani, Mahmood Ahmadi. 2026-07-25. Enhancing Error Detection Performance through Parallel CRC Computation on Multi-Core Architectures. https://arxiv.org/abs/2607.24849

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Reforge: Low-Latency Distributed GNN Serving with Selective Embedding Recomputation

Graph Neural Networks (GNNs) have been widely adopted for their ability to compute expressive node representations in graph datasets. However, serving GNNs on large graphs is challenging due to the high communication, computation, and memory overheads of constructing and executing computation graphs, which represent information flow across large neighborhoods. Existing approximation techniques in training can mitigate the overheads but, in serving, still lead to high latency and/or accuracy loss. To this end, we propose Reforge, a system that enables low-latency GNN serving for large graphs with minimal accuracy loss through two key ideas. First, Reforge employs selective recomputation of precomputed embeddings, which allows for reusing precomputed computation subgraphs while selectively recomputing a small fraction to minimize accuracy loss. Second, we develop computation graph parallelism, which reduces communication overhead by parallelizing the creation and execution of computation graphs across machines. Our evaluation with large graph datasets and GNN models shows that Reforge significantly outperforms state-of-the-art techniques.

cs.DC

Agentic AI Workload Characteristics

Agentic AI shifts LLM serving from isolated prompt-generation requests to stateful, multi-turn executions that repeatedly invoke the model, call tools, and grow context over time. This paper characterizes ReAct-style agents from both the LLM-serving and tool-execution perspectives using an end-to-end tracing infrastructure across reasoning and non-reasoning Gemma and Qwen configurations on five agentic benchmarks. Our study shows that agentic workloads are not simply long-prompt workloads: with effective context caching, most input tokens are reused across turns, making execution decode-dominated while increasing dependence on long-lived KV-cache state. We also find that tool use has a clear temporal structure, with agents shifting from read/explore behavior early in execution to execute/write behavior later. These results show that efficient agentic serving must jointly manage repeated model re-entry, persistent context state, and workload-dependent tool behavior.

cs.DC

Byzantine Causal Reliable Broadcast (BCRB) with Constant-Size Message Metadata

Asynchronous Byzantine Reliable Broadcast (BRB) is a fundamental primitive that guarantees agreement and validity in distributed systems subject to Byzantine faults, but it lacks ordering guarantees. In this paper, we address Byzantine Causal Reliable Broadcast (BCRB), which builds on BRB to enforce causal message ordering. We present a novel BCRB protocol that decouples causal ordering from the BRB layer, achieving constant-size $\mathcal{O}(1)$ message metadata overhead and $\mathcal{O}(n^2)$ communication word complexity as against $\mathcal{O}(n^3)$ communication word complexity of existing protocols; here $n$ is the number of processes. We present two variants of our protocol: a cryptographic version using a threshold encryption scheme and sequence gating, and its non-cryptographic version. In the cryptographic version, senders broadcast ciphertexts immediately, and decryption shares are piggybacked on out-of-band ACKs, preventing early decryption and front-running. In both versions, causal safety is achieved probabilistically. We evaluate the probability of causal safety violations using a random variable path analysis under independent exponential link delay distributions. We show that both variants satisfy liveness and the probability of weak safety violation is bounded by $\mathcal{O}(f^{-3}\cdot\ln^3 f)$, where $f$ is the upper bound on the number of Byzantine processes, and $f < n/3$ and $f=\mathcal{O}(n)$. Further, for the crypto version, we show that the probability of strong safety violation is bounded by $\mathcal{O}(f^{-1} \cdot \ln^2 f)$. We also show how to modify our two protocols to guarantee 100\% weak safety keeping $\mathcal{O}(1)$ message space overhead but with $\mathcal{O}(n^3)$ messages and $\mathcal{O}(n^3)$ communication word complexity.

cs.DC