The Morning Paper

SEPTEMBER 27, 2020

Furthermore, as hardware and compiler optimisations rapidly evolve, it is challenging even for a knowledgeable developer to keep up. The study is conducted using a suite of 7 real-world popular scientific applications, and two well-established benchmark suites: Miniaero solves the compressible Navier-Stokes equation. lines of code.

Benchmarking 101

Benchmarking Hardware Programming Code 101

All Things Distributed

NOVEMBER 21, 2018

Verifying benchmark claims. I picked these examples because they aren't operations that show up in standard data warehousing benchmarks, yet are meaningful parts of customer workloads. Verifying benchmark claims. I've noticed a troubling trend in vendor benchmarking claims over the past year.

Cloud 115

Cloud Benchmarking Performance AWS 115

HammerDB

OCTOBER 23, 2023

HammerDB uses stored procedures to achieve maximum throughput when benchmarking your database. HammerDB has always used stored procedures as a design decision because the original benchmark was implemented as close as possible to the example workload in the TPC-C specification that uses stored procedures.

Benchmarking 63

Benchmarking Database Network C++ 63

Scalegrid

JULY 13, 2020

Oracle requires more complex ongoing administration, as all database configurations must evolve in conjunction with the data schemas and custom code. Oracle support for hardware and software packages is typically available at 22% of their licensing fees. So Which Is Best?

Open Source 244

Open Source C++ Tuning Database 244

Brendan Gregg

MARCH 16, 2024

Apart from library code, maybe your application doesn't have frame pointers either, in which case everything is broken. Only in extreme circumstances does the cost (in processor time and I-cache footprint) translate to a tangible benefit - circumstances which usually resort to hand-coded assembly anyway.

Java 137

Java Cache Google Hardware 137

Percona

JUNE 22, 2023

Defining high availability In general terms, high availability refers to the continuous operation of a system with little to no interruption to end users in the event of hardware or software failures, power outages, or other disruptions. If a primary server fails, a backup server can take over and continue to serve requests.

Availability 132

Availability Database Open Source Hardware 132

John McCalpin

APRIL 25, 2023

I have a lot of historical data using my ReadOnly benchmark (as described in some of the earliest entries in this blog [link] A read-only access pattern removes the need to understand and explain the many complexities associated with the “streaming stores” typically used in the STREAM benchmark (e.g., Stay tuned!

Benchmarking 97

Benchmarking Cache Latency Tuning 97

Scalegrid

JANUARY 25, 2024

Key metrics like throughput, request latency, and memory utilization are essential for assessing Redis health, with tools like the MONITOR command and Redis-benchmark for latency and throughput analysis and MEMORY USAGE/STATS commands for evaluating memory. <code> 127.0.0.1:6379> <code> 127.0.0.1:6379>

Metrics 130

Metrics Monitoring Latency Cache 130

Scalegrid

DECEMBER 6, 2023

This type of database offers scalability with no downtime along with giving businesses control over what resources they use through customization capabilities such as choosing hardware infrastructure options or building security measures around it. These advantages come at an expense.

Database 130

Database Cloud Hardware Storage 130

Alex Russell

APRIL 29, 2021

As an engineer on a browser team, I'm privy to the blow-by-blow of various performance projects, benchmark fire drills, and the ways performance marketing (deeply) impacts engineering priorities. With each team, benchmarks lost are understood as bugs. is access to hardware devices. This is as it should be. Compression Streams.

Media 145

Media Games Education Engineering 145

Percona

AUGUST 22, 2023

Some of the most important elements include: No single point of failure (SPOF): You must eliminate any SPOF in the database environment, including any potential for an SPOF in physical or virtual hardware. Redundancy provides backups and safeguards against data loss in case of hardware failures. there cannot be high availability.

Availability 98

Availability Hardware Open Source Database 98

The Morning Paper

MAY 27, 2019

Last week we saw the benefits of rethinking memory and pointer models at the hardware level when it came to object storage and compression ( Zippads ). The protections are hardware implemented and cannot be forged in software. code is not given access to excessive capabilities. ASPLOS’19. CHERI implementation.

C++ 61

C++ Hardware Virtualization Benchmarking 61

Brendan Gregg

SEPTEMBER 25, 2021

The broken Java stacks turned out to be beneficial: They helped group together the os::javaTimeMillis() calls which otherwise might have have been scattered on top of different Java code paths, appearing as thin stacks everywhere. Without NMI, some kernel code paths (interrupts disabled) can't be profiled. But I'm not completely sure.

Speed 103

Speed Java AWS Virtualization 103

The Morning Paper

JUNE 27, 2019

Systems researchers are doing an excellent job improving the performance of 5-year old benchmarks, but gradually making it harder to explore innovative machine learning research ideas. Named dimensions improve readability by making it easier to determine how dimensions in the code correspond to the semantic dimensions described in,e.g.,

Systems 87

Systems Programming Tuning Innovation 87

HammerDB

JUNE 27, 2022

HammerDB is a software application for database benchmarking. It enables the user to measure database performance and make comparative judgements about database hardware and software. Databases are highly sophisticated software, and to design and run a fair benchmark workload is a complex undertaking. Derived Workloads.

Benchmarking 63

Benchmarking Open Source C++ Cache 63

HammerDB

JULY 6, 2024

In a recent project comparing systems for MariaDB performance, a user had originally been using a tool called sysbench-tpcc to compare hardware platforms before migrating to HammerDB. This is a brief post to highlight the metrics to use to do the comparison using a separate hardware platform for illustration purposes. hammerdbcli auto./scripts/tcl/maria/tprocc/maria_tprocc_build.tcl

C++ 52

C++ Hardware Benchmarking Virtualization 52

HammerDB

FEBRUARY 25, 2021

HammerDB is a load testing and benchmarking application for relational databases. However, it is crucial that the benchmarking application does not have inherent bottlenecks that artificially limits the scalability of the database. Basic Benchmarking Concepts. To benchmark a database we introduce the concept of a Virtual User.

Programming 68

Programming Benchmarking Virtualization C++ 68

HammerDB

NOVEMBER 22, 2021

This enables the user to compare and contrast performance across different benchmark scenarios. The events are colour coded and indexed in the graph to the wait event groups. Metrics view for benchmark. PostgreSQL Graphical Metrics. Install pg_stat_statements and pg_sentinel extensions.

Metrics 63

Metrics Benchmarking C++ Database 63

Alex Russell

OCTOBER 22, 2017

Budgets are scaled to a benchmark network & device. For this page to be done loading it needs to be responsive to user input — the “interactive” in “Time to Interactive” Browsers process user input by generating DOM events that application code listens to. Execute the script. Global Ground-Truth.

Performance 74

Performance Network Benchmarking Mobile 74

HammerDB

APRIL 19, 2023

GHz 4th Generation Intel Xeon Scalable processors (code-named Sapphire Rapids) Up to 20% higher compute performance than z1d instances Up to 50 Gbps of networking speed Up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (EBS) We can also verify these capabilities by running some simple benchmarks on the different subsystems.

Performance 55

Performance Benchmarking Cache Storage 55

HammerDB

JUNE 27, 2024

Arguably, the most common beginning errors with database benchmarking is for a user to select a single point of utilisation (usually overconfigured) and then extrapolate conclusions about system performance from this single point. Copy Code Copied Use a different Browser #!/bin/tclsh

C++ 52

C++ Performance Benchmarking Virtualization 52

SQL Performance

AUGUST 27, 2019

On August 7, 2019, AMD finally unveiled their new 7nm EPYC 7002 Series of server processors, formerly code-named "Rome" at the AMD EPYC Horizon Event in San Francisco. It will also use less power than a two-socket Intel server, with a lower hardware cost, and potentially lower licensing costs (for things like VMware).

Servers 52

Servers Benchmarking Virtualization Architecture 52

SQL Server According to Bob

SEPTEMBER 26, 2016

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.

Availability 40

Availability Servers Hardware Benchmarking 40

Abhishek Tiwari

DECEMBER 13, 2017

More importantly, if this works out well, this could lead to a radical improvement in performance by leveraging hardware trends such as GPUs and TPUs. The benchmarking was performed using 3 real-world data sets (weblogs, maps, and web-documents), and 1 synthetic dataset (lognormal). Learned indexes.

Artificial Intelligence 40

Artificial Intelligence Hardware Google Benchmarking 40

John McCalpin

APRIL 25, 2023

I have a lot of historical data using my ReadOnly benchmark (as described in some of the earliest entries in this blog [link] A read-only access pattern removes the need to understand and explain the many complexities associated with the “streaming stores” typically used in the STREAM benchmark (e.g., Stay tuned!

Benchmarking 40

Benchmarking Cache Latency Tuning 40

Brendan Gregg

SEPTEMBER 25, 2021

The broken Java stacks turned out to be beneficial: They helped group together the os::javaTimeMillis() calls which otherwise might have have been scattered on top of different Java code paths, appearing as thin stacks everywhere. Without NMI, some kernel code paths (interrupts disabled) can't be profiled.

Speed 52

Speed Java AWS Virtualization 52

John McCalpin

JANUARY 22, 2018

A peculiar throughput limitation on Intel’s Xeon Phi x200 (Knights Landing) Introduction: In December 2017, my colleague Damon McDougall (now at AMD) asked for help in porting the fused multiply-add example code from a Colfax report ( [link] ) to the Xeon Phi x200 (Knights Landing) processors here at TACC.

Latency 40

Latency Hardware Code Testing 40

John McCalpin

JANUARY 22, 2018

Introduction: In December 2017, my colleague Damon McDougall (now at AMD) asked for help in porting the fused multiply-add example code from a Colfax report ( [link] ) to the Xeon Phi x200 (Knights Landing) processors here at TACC. Instead, we found puzzle after puzzle. Instead, we found puzzle after puzzle.

Latency 40

Latency Hardware Code Testing 40

Brendan Gregg

SEPTEMBER 25, 2021

The broken Java stacks turned out to be beneficial: They helped group together the os::javaTimeMillis() calls which otherwise might have have been scattered on top of different Java code paths, appearing as thin stacks everywhere. Without NMI, some kernel code paths (interrupts disabled) can't be profiled. But I'm not completely sure.

Speed 40

Speed Java AWS Virtualization 40

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 anyone benchmarking MySQL with HammerDB it is important to understand the differences from sysbench workloads as HammerDB is targeted at a testing a different usage model from sysbench. Configure MySQL.

Best Practices 40

Best Practices Scalability Performance C++ 40

Percona

JULY 1, 2023

Understanding DBaaS DBaaS cloud services allow users to use databases without configuring physical hardware and infrastructure or installing software. Doing extensive benchmarks will be the subject of a future blog post. In any case, you should benchmark both RDS MySQL and Aurora before taking the decision to migrate.

AWS 52

AWS Database Serverless Storage 52

SQL Server According to Bob

JANUARY 11, 2020

Example 1: ​​ Hardware failure (CPU board) Battery backup on the caching controller maintained the data. Important Always consult with your hardware manufacturer for proper stable media strategies. Mirroring can be implemented at a software or hardware level.

Servers 40

Servers Cache Media Hardware 40

Alex Russell

JANUARY 30, 2024

HTML, CSS, images, and fonts can all be parsed and run at near wire speeds on low-end hardware, but JavaScript is at least three times more expensive, byte-for-byte. Most sorts of sites have shallow sessions, making up-front script costs hard to justify.

Performance 98

Performance Network Mobile Speed 98

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.

Tuning 52

Tuning Benchmarking Engineering C++ 52

SQL Server According to Bob

JANUARY 11, 2020

​​ The following ​​ code ​​ example ​​ shows ​​ the setting ​​ of ​​ values ​​ in ​​ illegal ​​ array positions. scid=kb ; en-us;828339 ) on the Microsoft Web site.

Servers 40

Servers Cache Database Media 40

Smashing Magazine

JANUARY 6, 2020

Is it worth exploring tree-shaking, scope hoisting, code-splitting, and all the fancy loading patterns with intersection observer, server push, clients hints, HTTP/2, service workers and — oh my — edge workers? It’s much easier to reach performance goals when the code base is fresh or is just being refactored.

Performance 112

Performance Cache Servers Network 112

Smashing Magazine

JANUARY 11, 2021

Have we optimized enough with tree-shaking, scope hoisting, code-splitting, and all the fancy loading patterns with intersection observer, progressive hydration, clients hints, HTTP/3, service workers and — oh my — edge workers? It’s much easier to reach performance goals when the code base is fresh or is just being refactored.

Performance 145

Performance Cache Media Metrics 145