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Description

There's no requirement to modify your coding practices or the methods you use to develop your projects. You can conduct profiling for applications that operate on multiple servers and involve various processes, providing clear insights into potential bottlenecks related to I/O, computational tasks, threading, or multi-process operations. You'll gain a profound understanding of the specific types of processor instructions that impact your overall performance. Additionally, you can monitor memory usage over time, allowing you to identify peak usage points and fluctuations throughout the entire memory landscape. Arm MAP stands out as a uniquely scalable profiler with low overhead, available both as an independent tool and as part of the comprehensive Arm Forge debugging and profiling suite. It is designed to assist developers of server and high-performance computing (HPC) software in speeding up their applications by pinpointing the root causes of sluggish performance. This tool is versatile enough to be employed on everything from multicore Linux workstations to advanced supercomputers. You have the option to profile realistic scenarios that matter the most to you while typically incurring less than 5% in runtime overhead. The user interface is interactive, fostering clarity and ease of use, making it well-suited for both developers and computational scientists alike, enhancing their productivity and efficiency.

Description

Zymtrace is an advanced platform for continuous profiling and observability that enables engineers to enhance the performance of contemporary computing workloads running on both CPUs and GPUs. It offers profound insights into system-level operations, revealing how applications, AI models, and infrastructure utilize computing resources, which empowers developers to pinpoint inefficiencies and performance obstacles without needing to alter their code or restart their systems. Utilizing eBPF-based profiling technology, zymtrace gathers performance data throughout the entire execution stack, ranging from high-level application code and runtime libraries to the Linux kernel and GPU instructions, thus facilitating a comprehensive analysis of diverse workloads. Furthermore, it effectively correlates GPU activities with the associated CPU code paths that initiate them, addressing a significant limitation of traditional observability tools that often regard GPUs as opaque entities, providing only superficial metrics. By bridging this gap, zymtrace enhances the overall understanding of performance dynamics in complex systems, ultimately guiding more informed optimization strategies.