O'Reilly

NOVEMBER 28, 2023

Even with cloud-based foundation models like GPT-4, which eliminate the need to develop your own model or provide your own infrastructure, fine-tuning a model for any particular use case is still a major undertaking. That pricing won’t be sustainable, particularly as hardware shortages drive up the cost of building infrastructure.

Open Source 106

Open Source Artificial Intelligence Google Infrastructure 106

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

Abhishek Tiwari

JULY 12, 2018

It can be used to power new analytics, insight, and product features. It can be used to power new analytics, insight, and product features. A data pipeline is a software which runs on hardware. The software is error-prone and hardware failures are inevitable. Data pipeline initiatives are generally unfinished projects.

Latency 63

Latency Analytics Scalability Engineering 63

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.

AWS 165

AWS Lambda Artificial Intelligence Mobile 165

O'Reilly Software

APRIL 4, 2018

The data shape will dictate capacity planning, tuning of the backbone, and scalability analysis for individual components. It enables unbounded scalability as more commodity or specialized hardware can be seamlessly added to existing clusters. What message process warranty level do we require? At least once? At most once? Exactly once?

Architecture 80

Architecture Scalability Google Operating System 80

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. Finally it is also important to note that this comparison is focused around OLTP based workloads, HammerDB also supports a TPC-H based workload for analytics with complex ad-hoc queries. innodb_file_per_table.

Best Practices 40

Best Practices Scalability Performance C++ 40

O'Reilly

OCTOBER 11, 2022

Andrew Ng , Christopher Ré , and others have pointed out that in the past decade, we’ve made a lot of progress with algorithms and hardware for running AI. Our current set of AI algorithms are good enough, as is our hardware; the hard problems are all about data. Is special-purpose training to fine-tune a model’s behavior an option?

Games 114

Games Healthcare Processing Retail 114

HammerDB

FEBRUARY 25, 2021

For the TPROC-H workload this is all we need the queries are long-running analytics queries so once executed on the database do not need to wait for the benchmarking client. and the following from TPROC-H. select top 100. s_acctbal, s_name, n_name, p_partkey, p_mfgr, s_address, s_phone, s_comment. where p_partkey = ps_partkey.

Programming 67

Programming Benchmarking Virtualization C++ 67

Percona

AUGUST 30, 2018

Because recognizing if the workload is read intensive or write intensive will impact your hardware choices, database configuration as well as what techniques you can apply for performance optimization and scalability. To look at timing information from query point of view, we want to look at query analytics. Why should you care?

Benchmarking 47

Benchmarking Database Operating System Architecture 47

High Scalability

NOVEMBER 25, 2019

Eventually, we resorted to caching the events in memory for a short duration and also tuning the GC settings on those nodes as we are doing a lot of young generation collections. Do you implement web analytics? We use Google Analytics, Mixpanel, Flurry to measure feature usage. How are software and hardware upgrades rolled out?

Architecture 52

Architecture Cache Azure Storage 52

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. In this article, we will look at how this can improve the reporting/analytical query performance in MySQL. With faster disks (i.e. SSD) we can’t utilize the full potential of IOPS with just one thread.

Cache 46

Cache C++ AWS Airlines 46