Percona

NOVEMBER 3, 2023

Rather than listing the concepts, function calls, etc, available in Citus, which frankly is a bit boring, I’m going to explore scaling out a database system starting with a single host. I won’t cover all the features but show just enough that you’ll want to see more of what you can learn to accomplish for yourself.

Database 102

Database Benchmarking Latency C++ 102

The Netflix TechBlog

AUGUST 30, 2021

Complementing the hardware is the software on the RAE and in the cloud, and bridging the software on both ends is a bi-directional control plane. For example, when running tests, the state of the device will change from “available for testing” to “in test.” In this blog post, we will focus on the latter feature set.

Latency 213

Latency Traffic Transportation Hardware 213

Adrian Cockcroft

JUNE 21, 2022

I became the Sun UK local specialist in performance and hardware, and as Sun transitioned from a desktop workstation company to sell high end multiprocessor servers I was helping customers find and fix scalability problems. We had specializations in hardware, operating systems, databases, graphics, etc. that a lot of people used.

Tuning 52

Tuning Benchmarking Engineering C++ 52

Percona

APRIL 17, 2023

The main objective of this post is to share my experience over the past years tuning MongoDB and centralize the diverse sources that I crossed in this journey in a unique place. There is an issue with this, which causes the OS to swap even with memory available. Spoiler alert: This post focuses on MongoDB 3.6.X 25.84 - Total 21.04

Best Practices 52

Best Practices Design Tuning Database 52

The Morning Paper

JUNE 13, 2019

HotOS’19 is presenting me with something of a problem as there are so many interesting looking papers in the proceedings this year it’s going to be hard to cover them all! Different hardware architectures (CPUs, GPUs, TPUs, FPGAs, ASICs, …) offer different performance and cost trade-offs. HotOS’19.

Hardware 58

Hardware Latency Serverless Energy 58

SQL Performance

MARCH 17, 2020

Back in 2014, I wrote an article called Performance Tuning the Whole Query Plan. I will be looking for distinct values in the BountyAmount column of the dbo.Votes table, presented in bounty amount order ascending. It has 32GB RAM, with 24GB available to the SQL Server 2019 instance. Test Environment. Final Thoughts.

Servers 86

Servers Tuning Database Efficiency 86

The Morning Paper

MARCH 17, 2020

One thing they all had in common is an evaluation using some kind of simulation of the expected behaviour of NVDIMMs, because the real thing wasn’t yet available. Based on these findings, the authors present four guidelines to get the best performance out of this memory today. But now it is! Optane DIMMs are here!

Scalability 59

Scalability Latency Cache Media 59

HammerDB

OCTOBER 18, 2019

cpupower frequency-info analyzing CPU 0: driver: intel_pstate CPUs which run at the same hardware frequency: 0 CPUs which need to have their frequency coordinated by software: 0 maximum transition latency: Cannot determine or is not supported. hardware limits: 1000 MHz - 4.00 hardware limits: 1000 MHz - 4.00

Benchmarking 63

Benchmarking Performance Hardware C++ 63

HammerDB

JANUARY 5, 2019

As the chart shows because we know that both HammerDB and the implementation of the TPC-C workload scales then we can determine that with this particular database engine both the software and hardware scales as well. In all cases this is random data so presents no security challenges. can you be sure that it scales?

Benchmarking 40

Benchmarking Database Social Media Scalability 40

Brendan Gregg

SEPTEMBER 25, 2021

As a Xen guest, this profile was gathered using perf(1) and the kernel's software cpu-clock soft interrupts, not the hardware NMI. Checking those available: $ cat /sys/devices/system/clocksource/clocksource0/available_clocksource. Theory (A) is most likely based on the frame widths in the flame graph. But I'm not completely sure.

Speed 126

Speed Java AWS Virtualization 126

O'Reilly Software

APRIL 4, 2018

Fast forward to the present day and we find ourselves in a world where the number of connected devices is constantly increasing. The data shape will dictate capacity planning, tuning of the backbone, and scalability analysis for individual components. What message process warranty level do we require? At least once? At most once?

Architecture 80

Architecture Scalability Google Operating System 80

SQL Performance

MARCH 8, 2021

This can make it difficult to draw sound performance-tuning conclusions. This uses hardware, typically a crystal oscillator, that produces ticks at a very high constant rate regardless of processor speed, power settings, or anything of that nature. SQL Server uses the high-precision QueryPerformanceCounter API to capture timing data.

Servers 95

Servers Tuning Architecture Processing 95

HammerDB

OCTOBER 12, 2018

As is also the case this limitation is at the database level (especially the storage engine) rather than the hardware level. For this reason sysbench presents a vastly more simplified workload than HammerDB. . driver: intel_pstate CPUs which run at the same hardware frequency: 0 . hardware limits: 1000 MHz - 3.80

Best Practices 40

Best Practices Scalability Performance C++ 40

Sutter's Mill

MAY 28, 2012

Three weeks ago , we hosted another three-day face-to-face meeting for SG1 and SG4 – and at nearly 40 people the SG1 attendance rivaled that of a normal full ISO C++ meeting, with a who’s-who of the world’s concurrency and parallelism experts in attendance and further proposal presentations from companies like IBM, Intel, and Microsoft.

C++ 40

C++ Hardware Best Practices Tuning 40

John McCalpin

JANUARY 22, 2018

Dr. Damon McDougall gave a short presentation on this study at the IXPUG 2018 Fall Conference ( pdf ) — I originally wrote these notes to help organize my thoughts as we were preparing the IXPUG presentation, and later decided that the extra details contained here are interesting enough for me to post it.

Latency 40

Latency Hardware Code Testing 40

SQL Server According to Bob

JANUARY 11, 2020

​​ Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information presented after the date of publication. This White Paper is for informational purposes only.

Servers 40

Servers Cache Media Hardware 40

Brendan Gregg

SEPTEMBER 25, 2021

As a Xen guest, this profile was gathered using perf(1) and the kernel's software cpu-clock soft interrupts, not the hardware NMI. As for tracesys: I investigated the overhead for other syscalls and found it to be negligible, and before I returned to work on it further the kernel code paths changed and it was no longer present in the stacks.

Speed 40

Speed Java AWS Virtualization 40

Brendan Gregg

SEPTEMBER 5, 2017

What follows are topics that may be of interest to anyone looking to migrate their systems and skillset: scan these to find topics that interest you. ## ZFS ZFS is available for Linux via the [zfsonlinux] and [OpenZFS] projects, and more recently was included in Canonical's Ubuntu Linux distribution: Ubuntu Xenial 16.04 LTS (April 2016).

Virtualization 76

Virtualization AWS Engineering Hardware 76

SQL Server According to Bob

JANUARY 11, 2020

​​ Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information presented after the date of publication. This White Paper is for informational purposes only.

Servers 40

Servers Cache Database Media 40

Smashing Magazine

AUGUST 22, 2021

Additionally, even if we knew the available physical bandwidth, that wouldn’t mean we could use all of it ourselves. Several users are typically active on a network concurrently, each of whom need a fair share of the available bandwidth. More in-depth information is available. What Does It All Mean? as well!

Performance 105

Performance Network Latency Servers 105

All Things Distributed

NOVEMBER 30, 2016

Effectively applying AI involves extensive manual effort to develop and tune many different types of machine learning and deep learning algorithms (e.g. automatic speech recognition, natural language understanding, image classification), collect and clean the training data, and train and tune the machine learning models. Amazon Lex.

AWS 166

AWS Lambda Artificial Intelligence Mobile 166