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This was a chance to talk about other things I've been working on, such as the present and future of hardware performance. BBR: Congestion-Based Congestion Control,” [link] 2016 - [Gregg 16] Brendan Gregg, “Unikernel Profiling: Flame Graphs from dom0,” [link] Jan 2016 - [Gregg 16b] Brendan Gregg, “Linux 4.X Ford, et al., “TCP
My personal opinion is that I don't see a widespread need for more capacity given horizontal scaling and servers that can already exceed 1 Tbyte of DRAM; bandwidth is also helpful, but I'd be concerned about the increased latency for adding a hop to more memory. Ford, et al., “TCP
Back in 2016, I gave a talk outlining the causes and effects of the terrible performance of web apps built using popular tools on the fastest-growing device segment: low-end to mid-range Android phones. In 2016, Jio swept over the subcontinent like a monsoon dropping a torrent of 4G infrastructure and free data rather than rain.
When we released Always On Availability Groups in SQL Server 2012 as a new and powerful way to achieve high availability, hardware environments included NUMA machines with low-end multi-core processors and SATA and SAN drives for storage (some SSDs). As we moved towards SQL Server 2014, the pace of hardware accelerated.
They can run applications in Sweden, serve end users across the Nordics with lower latency, and leverage advanced technologies such as containers, serverless computing, and more. The second platform is a managed IoT cloud with customer-facing applications and data management, which went live in 2016.
” This paper describes a “far memory” system that has been in production deployment at Google since 2016. This boils down to a single digit µs latency toleration in the tail for far memory, and in addition to security and privacy concerns, rules out remote memory solutions. Evaluation.
“Memory Bandwidth and System Balance in HPC Systems” If you are planning to attend the SuperComputing 2016 conference in Salt Lake City next month, be sure to reserve a spot on your calendar for my talk on Wednesday afternoon (4:15pm-5:00pm).
This was a chance to talk about other things I've been working on, such as the present and future of hardware performance. BBR: Congestion-Based Congestion Control,” [link] 2016 - [Gregg 16] Brendan Gregg, “Unikernel Profiling: Flame Graphs from dom0,” [link] Jan 2016 - [Gregg 16b] Brendan Gregg, “Linux 4.X Ford, et al., “TCP
LTS (April 2016). I wrote about it in a previous post, [DTrace for Linux 2016]. Here's some output from my zfsdist tool, in bcc/BPF, which measures ZFS latency as a histogram on Linux: # zfsdist. Tracing ZFS operation latency. The hardest part on Linux is now done: kernel support. Hit Ctrl-C to end. ^C
At the time of the last Confluence run, the gap had stretched to nearly 1000 APIs, doubling since 2016. For heavily latency-sensitive use-cases like WebXR, this is a critical component in delivering a good experience. is access to hardware devices. Some commenters appear to confuse unlike hardware for differences in software.
My personal opinion is that I don't see a widespread need for more capacity given horizontal scaling and servers that can already exceed 1 Tbyte of DRAM; bandwidth is also helpful, but I'd be concerned about the increased latency for adding a hop to more memory. Ford, et al., “TCP
A message-oriented implementation requires an efficient messaging backbone that facilitates the exchange of data in a reliable and secure way with the lowest latency possible. In 2016, Apache Spark introduced Structured Streaming , a new streaming engine based on the SparkSQL abstractions and runtime optimizations.
It simulates a link with a 400ms RTT and 400-600Kbps of throughput (plus latency variability and simulated packet loss). Simulated packet loss and variable latency, however, can make benchmarking extremely difficult and slow. Our baseline, then, should probably trade lower throughput/higher-latency for packet loss.
In the latest (October 2016) revision of Intel’s Instruction Extensions Programming Reference , Intel has disclosed a fairly dramatic departure from these “traditional” approaches. With 2 FMA units that have 5-cycle latency, the code must implement at least 2*5=10 independent accumulators in order to avoid stalls.
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