http://queue.acm.org/listing.cfm?item_topic=Performance&qc_type=topics_list&filter=Performance&page_title=Performance&order=desc http://queue.acm.org/detail.cfm?id=3291278 As more and more software moves off the desktop and into data centers, and more and more cell phones use server requests as the other half of apps, observation tools for large-scale distributed transaction systems are not keeping up. This makes it tempting to look under the lamppost using simpler tools. You will waste a lot of high-pressure time following that path when you have a sudden complex performance crisis. Instead, know what each tool you use is blind to, know what information you need to understand a performance problem, and then look for tools that can actually observe that information directly. Performance Tue, 06 Nov 2018 14:51:33 GMT Richard L. Sites 3291278 http://queue.acm.org/detail.cfm?id=3231573 This installment of Research for Practice features a curated selection from Gustavo Alonso, who provides an overview of recent developments utilizing FPGAs (field-programmable gate arrays) in datacenters. As Moore's Law has slowed and the computational overheads of datacenter workloads such as model serving and data processing have continued to rise, FPGAs offer an increasingly attractive point in the trade-off between power and performance. Gustavo's selections highlight early successes and practical deployment considerations that inform the ongoing, high-stakes debate about the future of datacenter- and cloud-based computation substrates. Performance Tue, 05 Jun 2018 14:13:40 GMT Gustavo Alonso 3231573 http://queue.acm.org/detail.cfm?id=3229201 This article presents equations that relate to workload utilization scaling at a per-DVFS subsystem level. A relation between frequency, utilization, and scale factor (which itself varies with frequency) is established. The verification of these equations turns out to be tricky, since inherent to workload, the utilization also varies seemingly in an unspecified manner at the granularity of governance samples. Thus, a novel approach called histogram ridge trace is applied. Quantifying the scaling impact is critical when treating DVFS as a building block. Typical application includes DVFS governors and or other layers that influence utilization, power, and performance of the system. The scope here though, is limited to demonstrating well-quantified and verified scaling equations. Performance Thu, 24 May 2018 17:48:56 GMT Noor Mubeen 3229201 http://queue.acm.org/detail.cfm?id=3178371 Monitoring can seem quite overwhelming. The most important thing to remember is that perfect should never be the enemy of better. DevOps enables highly iterative improvement within organizations. If you have no monitoring, get something; get anything. Something is better than nothing, and if you've embraced DevOps, you've already signed up for making it better over time. Performance Mon, 08 Jan 2018 16:05:18 GMT Theo Schlossnagle 3178371 http://queue.acm.org/detail.cfm?id=2977741 Google's Chrome web browser strives to deliver a smooth user experience. An animation will update the screen at 60 FPS (frames per second), giving Chrome around 16.6 milliseconds to perform the update. Within these 16.6 ms, all input events have to be processed, all animations have to be performed, and finally the frame has to be rendered. A missed deadline will result in dropped frames. These are visible to the user and degrade the user experience. Such sporadic animation artifacts are referred to here as jank. This article describes an approach implemented in the JavaScript engine V8, used by Chrome, to schedule garbage-collection pauses during times when Chrome is idle. This approach can reduce user-visible jank on real-world web pages and results in fewer dropped frames. Performance Tue, 26 Jul 2016 16:37:27 GMT Ulan Degenbaev, Jochen Eisinger, Manfred Ernst, Ross McIlroy, Hannes Payer 2977741 http://queue.acm.org/detail.cfm?id=2789974 "We often see more than 100 percent speedup efficiency!" came the rejoinder to the innocent reminder that you can't have more than 100 percent of anything. But this was just the first volley from software engineers during a presentation on how to quantify computer system scalability in terms of the speedup metric. In different venues, on subsequent occasions, that retort seemed to grow into a veritable chorus that not only was superlinear speedup commonly observed, but also the model used to quantify scalability for the past 20 years failed when applied to superlinear speedup data. Performance Thu, 04 Jun 2015 20:08:33 GMT Neil Gunther, Paul Puglia, Kristofer Tomasette 2789974 http://queue.acm.org/detail.cfm?id=2576968 When you call functions in an API, you expect them to work correctly; sometimes this expectation is called a contract between the caller and the implementation. Callers also have performance expectations about these functions, and often the success of a software system depends on the API meeting these expectations. So there's a performance contract as well as a correctness contract. The performance contract is usually implicit, often vague, and sometimes breached (by caller or implementation). How can this aspect of API design and documentation be improved? Performance Thu, 30 Jan 2014 15:37:49 GMT Robert Sproull, Jim Waldo 2576968 http://queue.acm.org/detail.cfm?id=2446236 The overwhelming evidence indicates that a Web site's performance (speed) correlates directly to its success, across industries and business metrics. With such a clear correlation (and even proven causation), it is important to monitor how your Web site performs. So, how fast is your Web site? Performance Mon, 04 Mar 2013 20:01:36 GMT Patrick Meenan 2446236 http://queue.acm.org/detail.cfm?id=2413037 Performance issues can be complex and mysterious, providing little or no clue to their origin. In the absence of a starting point, performance issues are often analyzed randomly: guessing where the problem may be and then changing things until it goes away. While this can deliver results it can also be time-consuming, disruptive, and may ultimately overlook certain issues. This article describes system-performance issues and the methodologies in use today for analyzing them, and it proposes a new methodology for approaching and solving a class of issues. Performance Tue, 11 Dec 2012 03:03:22 GMT Brendan Gregg 2413037 http://queue.acm.org/detail.cfm?id=2282337 Application performance is directly affected by the hardware resources that the application requires, the degree to which such resources are available, and how the operating system addresses its requirements with regard to the other processes in the system. Ideally, an application would have access to all the resources it could use and be allowed to complete its work without competing with any other activity in the system. In a world of highly shared hardware resources and generalpurpose, time-share-based operating systems, however, no guarantees can be made as to how well resourced an application will be. Performance Thu, 14 Jun 2012 00:03:47 GMT Rafael Vanoni Polanczyk 2282337