arXiv subjects

Alejandro Cano

Publications and source records attributed to Alejandro Cano.

6 recordsLinked to original sources

arXiv2026

Resource Allocation in HyperX Networks

As high-performance computing systems scale in size and complexity, efficient resource management is essential to minimize communication overhead. The HyperX is a richly connected, low-diameter network that offers a scalable and cost-effective alternative to traditional topologies. However, resource allocation in HyperX remains underexplored, and strategies designed for networks like Torus, Fat-tree, or Dragonfly do not directly transfer. In this work, we propose and formalize several resource allocation strategies for HyperX networks, categorized into linear, geometric, and stochastic functions. We characterize these strategies theoretically by analyzing their topological properties, including dilation, convexity, and partition bandwidth.Furthermore, we conduct an exhaustive experimental evaluation using synthetic traffic and application communication kernels to assess the impact of these strategies on performance under different routing algorithms. Our results indicate that partition bandwidth and switch locality are decisive factors in mitigating interferences. Notably, the Diagonal allocation strategy, which is not convex, consistently outperforms traditional approaches in most scenarios. Finally, we provide a set of lessons learned to guide the implementation of resource allocation policies in HPC systems based on HyperX networks.

cs.DC↗

arXiv2026

Extreme-Scale Interconnection Networks

Extreme-scale data centers are the backbone of next-generation computing, enabling breakthroughs in science, artificial intelligence, and global innovation through unprecedented processing power and scalability. This work examines leaf-spine network topologies that offer extreme scalability--connecting a vast number of endpoints--while delivering strong performance at low cost. It takes as a starting point two alternatives to the widely used Fat-Tree topology: the Orthogonal Fat-Tree and the Random Folded Clos. The resulting Multipass Random Leaf-Spine (MRLS) networks inherit their advantages and surpass Fat-Trees in both throughput and flexibility. To fully leverage the topological properties of these networks, various non-minimal routing strategies are considered. An exhaustive evaluation using an interconnection network simulator provides insight into the trade-offs and scalability of these topologies under realistic conditions, positioning them as a promising solution for extreme-scale systems. The MRLS achieves a 50% speedup against a Fat-Tree for an All2All collective comprising 100k endpoints, and 100% against Dragonfly networks for the same collective.

cs.NI↗

arXiv2025

Deadlock-free routing for Full-mesh networks without using Virtual Channels

High-radix, low-diameter networks like HyperX and Dragonfly use a Full-mesh core, and rely on multiple virtual channels (VCs) to avoid packet deadlocks in adaptive routing. However, VCs introduce significant overhead in the switch in terms of area, power, and design complexity, limiting the switch scalability. This paper starts by revisiting VC-less routing through link ordering schemes in Full-mesh networks, which offer implementation simplicity but suffer from performance degradation under adversarial traffic. Thus, to overcome these challenges, we propose TERA (Topology-Embedded Routing Algorithm), a novel routing algorithm which employs an embedded physical subnetwork to provide deadlock-free non-minimal paths without using VCs. In a Full-mesh network, TERA outperforms link ordering routing algorithms by 80% when dealing with adversarial traffic, and up to 100% in application kernels. Furthermore, compared to other VC-based approaches, it reduces buffer requirements by 50%, while maintaining comparable latency and throughput. Lastly, early results from a 2D-HyperX evaluation show that TERA outperforms state-of-the-art algorithms that use the same number of VCs, achieving performance improvements of up to 32%.

cs.DC↗

arXiv2025

Generative Artificial Intelligence-Supported Pentesting: A Comparison between Claude Opus, GPT-4, and Copilot

The advent of Generative Artificial Intelligence (GenAI) has brought a significant change to our society. GenAI can be applied across numerous fields, with particular relevance in cybersecurity. Among the various areas of application, its use in penetration testing (pentesting) or ethical hacking processes is of special interest. In this paper, we have analyzed the potential of leading generic-purpose GenAI tools-Claude Opus, GPT-4 from ChatGPT, and Copilot-in augmenting the penetration testing process as defined by the Penetration Testing Execution Standard (PTES). Our analysis involved evaluating each tool across all PTES phases within a controlled virtualized environment. The findings reveal that, while these tools cannot fully automate the pentesting process, they provide substantial support by enhancing efficiency and effectiveness in specific tasks. Notably, all tools demonstrated utility; however, Claude Opus consistently outperformed the others in our experimental scenarios.

cs.CR↗

arXiv2024

Achieving High-Performance Fault-Tolerant Routing in HyperX Interconnection Networks

Interconnection networks are key actors that condition the performance of current large datacenter and supercomputer systems. Both topology and routing are critical aspects that must be carefully considered for a competitive system network design. Moreover, when daily failures are expected, this tandem should exhibit resilience and robustness. Low-diameter networks, including HyperX, are cheaper than typical Fat Trees. But, to be really competitive, they have to employ evolved routing algorithms to both balance traffic and tolerate failures. In this paper, SurePath, an efficient fault-tolerant routing mechanism for HyperX topology is introduced and evaluated. SurePath leverages routes provided by standard routing algorithms and a deadlock avoidance mechanism based on an Up/Down escape subnetwork. This mechanism not only prevents deadlock but also allows for a fault-tolerant solution for these networks. SurePath is thoroughly evaluated in the paper under different traffic patterns, showing no performance degradation under extremely faulty scenarios.

cs.DC↗

arXiv2023

Analysing Mechanisms for Virtual Channel Management in Low-Diameter networks

To interconnect their growing number of servers, current supercomputers and data centers are starting to adopt low-diameter networks, such as HyperX, Dragonfly and Dragonfly+. These emergent topologies require balancing the load over their links and finding suitable non-minimal routing mechanisms for them becomes particularly challenging. The Valiant load balancing scheme is a very popular choice for non-minimal routing. Evolved adaptive routing mechanisms implemented in real systems are based on this Valiant scheme. All these low-diameter networks are deadlock-prone when non-minimal routing is employed. Routing deadlocks occur when packets cannot progress due to cyclic dependencies. Therefore, developing efficient deadlock-free packet routing mechanisms is critical for the progress of these emergent networks. The routing function includes the routing algorithm for path selection and the buffers management policy that dictates how packets allocate the buffers of the switches on their paths. For the same routing algorithm, a different buffer management mechanism can lead to a very different performance. Moreover, certain mechanisms considered efficient for avoiding deadlocks, may still suffer from hard to pinpoint instabilities that make erratic the network response. This paper focuses on exploring the impact of these buffers management policies on the performance of current interconnection networks, showing a 90\% of performance drop if an incorrect buffers management policy is used. Moreover, this study not only characterizes some of these undesirable scenarios but also proposes practicable solutions.

cs.AR↗