ACM Sigarch

OCTOBER 12, 2020

These, let’s call them metal languages , include FORTRAN (introduced in 1957), C (1972), and C++ (1985). Programmers continue to write applications in them, and they continue to evolve: the just approved C++20 standard is the latest example. Are caches large enough for this code? As Leiserson et al.

C++ 108

C++ Benchmarking Hardware Architecture 108

Percona

MAY 1, 2023

Key areas include: Configuration parameter tuning : This tuning involves altering variables such as memory allocation, disk I/O settings, and concurrent connections based on specific hardware and requirements. This not only results in cost savings by minimizing hardware requirements but also has the potential to decrease cloud expenses.

Tuning 52

Tuning Efficiency Database Performance 52

HammerDB

APRIL 19, 2023

This all sounded very similar to HammerDB TPROC-C workload (we will look at HammerDB TPROC-H (OLAP) another time), so it is easy for any reader to think both workloads are about the same. By default, HammerDB is designed to take advantage of database system caching mechanisms such as buffer caches, query caches, or statement caches.

Performance 54

Performance Benchmarking Cache Storage 54

Brendan Gregg

AUGUST 18, 2019

C @ns: [256, 512) 10900 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ | [512, 1k) 18291 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@| [1k, 2k) 4998 |@@@@@@@@@@@@@@ | [2k, 4k) 57 | | [4k, 8k) 117 | | [8k, 16k) 48 | | [16k, 32k) 109 | | [32k, 64k) 3 | |. hardware Hardware counter-based instrumentation. Hit Ctrl-C to end. ^C

Latency 68

Latency C++ Cache Programming 68

The Morning Paper

NOVEMBER 5, 2019

Breaking that assumption allowed Ceph to introduce a new storage backend called BlueStore with much better performance and predictability, and the ability to support the changing storage hardware landscape. But let’s take a quick look at the changing hardware landscape before we go on… The changing hardware landscape.

Storage 64

Storage Systems Hardware Efficiency 64

The Morning Paper

DECEMBER 8, 2019

Byte-addressable non-volatile memory,) NVM will fundamentally change the way hardware interacts, the way operating systems are designed, and the way applications operate on data. The beauty of persistent memory is that we can use memory layouts for persistent data (with some considerations for volatile caches etc. What about security?

Hardware 56

Hardware Programming Media Storage 56

All Things Distributed

SEPTEMBER 20, 2013

Not everybody agreed that the "N-ary Storage Model" (NSM) was the best approach for all workloads but it stayed dominant until hardware constraints, especially on caches, forced the community to revisit some of the alternatives. The first practical modern implementation is probably C-Store by Stonebraker, et al.

Storage 87

Storage Hardware Cache C++ 87

ScaleOut Software

JULY 27, 2018

Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities. Application developers often deploy IMDGs as a distributed cache that sits between an application and its database; the IMDG offloads ephemeral data from the database.

Scalability 40

Scalability Cache Airlines Healthcare 40

ScaleOut Software

JULY 27, 2018

Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities. Application developers often deploy IMDGs as a distributed cache that sits between an application and its database; the IMDG offloads ephemeral data from the database.

Scalability 40

Scalability Cache Airlines Healthcare 40

Smashing Magazine

JANUARY 11, 2021

Build Optimizations JavaScript modules, module/nomodule pattern, tree-shaking, code-splitting, scope-hoisting, Webpack, differential serving, web worker, WebAssembly, JavaScript bundles, React, SPA, partial hydration, import on interaction, 3rd-parties, cache. This improves page load time and caching during navigations.

Performance 145

Performance Cache Media Metrics 145

John McCalpin

NOVEMBER 5, 2016

So consider the dense matrix multiplication operation C += A*B, where A, B, and C are dense square matrices of order N, and the matrix multiplication operation is equivalent to the pseudo-code: for (i=0; i<N; i++) { for (j=0; j<N; j++) { for (k=0; k<N; k++) { C[i][j] += A[i][k] * B[k][j]; } } }.

Cache 40

Cache C++ Latency Hardware 40

Percona

JANUARY 17, 2019

On multi-core machines – which is the majority of the hardware nowadays – and in the cloud, we have multiple cores available for use. Aurora Parallel Query response time (for queries which can not use indexes) can be 5x-10x better compared to the non-parallel fully cached operations. The second and third run used the cached data.

Cache 47

Cache C++ AWS Airlines 47

SQL Server According to Bob

DECEMBER 18, 2018

Device level flushing may have an impact on your I/O caching, read ahead or other behaviors of the storage system. FILE_FLAG_NO_BUFFERING is the Win32, CreateFile API flags and attributes setting to bypass file system cache. FILE_FLAG_NO_BUFFERING is the Win32, CreateFile API flags and attributes setting to bypass file system cache.

Servers 90

Servers Media Cache Storage 90

Smashing Magazine

JANUARY 6, 2020

On the other hand, we have hardware constraints on memory and CPU due to JavaScript parsing times (we’ll talk about them in detail later). Gatsby (React), Vuepress (Vue) Preact CLI , and PWA Starter Kit provide reasonable defaults for fast loading out of the box on average mobile hardware. ??Also,

Performance 145

Performance Cache Network Metrics 145

Smashing Magazine

JANUARY 7, 2019

On the other hand, we have hardware constraints on memory and CPU due to JavaScript parsing times (we’ll talk about them in detail later). Gatsby.js (React), Preact CLI , and PWA Starter Kit provide reasonable defaults for fast loading out of the box on average mobile hardware. Image credit: Addy Osmani ) ( Large preview ).

Performance 103

Performance Cache Metrics Network 103

Smashing Magazine

JUNE 18, 2020

Flutter isn’t that, though: it runs natively on each platform, and it means each app runs just like it would run if it were written in Java/Kotlin or Objective-C/Swift on Android and iOS, pretty much. You need to know that because this implies that you need to take care of the many differences between these very diverse platforms.

Storage 93

Storage Mobile Website Java 93

Randon ASCII

FEBRUARY 25, 2018

In this particular investigation, which spanned twenty months, we suspected hardware failure, compiler bugs, linker bugs, and other possibilities. Jumping too quickly to blaming hardware or build tools is a classic mistake, but in this case the mistake was that we weren’t thinking big enough. failure rate.

Programming 79

Programming Hardware Cache Code 79

The Morning Paper

DECEMBER 1, 2019

Memory might be durable, but… …it is expected that caches and registers will remain volatile. Plus ça change, plus c’est la même chose. So, we’re going to need to take care that everything we say is committed is truly durable, and that we can recover to a consistent state following a crash.

Efficiency 60

Efficiency Cache C++ Performance 60

Highly Scalable

SEPTEMBER 18, 2012

A database should accommodate itself to different data distributions, cluster topologies and hardware configurations. C) In the previous schema, failures can be handled better using the hinted handoff technique [8]. Consider an example: there are 3 nodes A, B, and C and increment operation was applied 3 times, once per node.

Database 213

Database Latency C++ Scalability 213

The Morning Paper

APRIL 2, 2019

In this context it means there are no external dependencies on e.g. secrets, trusted hardware modules, or special instructions (e.g. A system comprises c connected devices, where device i has random access memory and processor registers. The word “unconditionally” from the paper title is also highly significant here.

Software 40

Software Software Programming Hardware 40

High Scalability

NOVEMBER 25, 2019

Edge caching. In general, Egnyte connect architecture shards and caches data at different levels based on: Amount of data. Nginx for disk based caching. We use different types of caching techniques depending on the problem statements. Disk based caching. Hybrid Sync. On prem data processing. Offline access.

Architecture 52

Architecture Cache Azure Storage 52

SQL Server According to Bob

JANUARY 11, 2020

Character POS ASCII Value Formula Value A 1 65 67 C 2 67 69 Checksum 136 Comparing ​​ the checksum values indicates ​​ that the values do not match and ​​ damage ​​ has occurred to the data.

Servers 40

Servers Cache Database Media 40

The Morning Paper

SEPTEMBER 12, 2019

SQL provides a declarative programming interface, below which the system itself can figure out the most effective execution plans based on data size and statistics, layout, compute hardware etc. The implementations require both SQL and also some UDFs written in C++. Be careful what you ask for (materialize).

Network 44

Network Database Programming Hardware 44

Smashing Magazine

AUGUST 22, 2021

Some examples of the latter are heavily cached websites, as well as single-page apps that periodically fetch small updates via APIs and other protocols such as DNS-over-QUIC. Let’s contemplate what would happen if A, B, and C were all render-blocking resources. This multiplexing can happen in many different ways. Large preview ).

Performance 105

Performance Network Latency Servers 105