Remove Architecture Remove Benchmark Remove Capacity Remove Management
article thumbnail

TPUs vs. GPUs: What’s the Difference?

Pure Storage

GPUs are generally faster than CPUs for deep learning tasks, but the specialized architecture of TPUs often allows them to be faster than GPUs. GPUs, while powerful, tend to consume more power, especially when operating at maximum capacity. product recognition in inventory management). medical image analysis) and retail (e.g.,

article thumbnail

TPUs vs. GPUs: What’s the Difference?

Pure Storage

GPUs are generally faster than CPUs for deep learning tasks, but the specialized architecture of TPUs often allows them to be faster than GPUs. GPUs, while powerful, tend to consume more power, especially when operating at maximum capacity. product recognition in inventory management). medical image analysis) and retail (e.g.,

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Demystifying Storage Complexity: The Hidden Tradeoffs with Some New Storage Solutions

Pure Storage

Unfortunately, real-world implementations proved SDS impractical due to complexity of management and operation, unpredictable performance, and reliability and support. In this blog, we will cover the enduring storage management burden that tends to follow the implementation of these solutions.

article thumbnail

Simplify Elastic Operations without Compromising Data Searchability Using FlashBlade

Pure Storage

Hadoop) means that growing capacity requires higher node counts and therefore growing complexity. What we really want is a way to grow capacity 10x without also adding 10x operational overhead. The results presented here show queries against the frozen tier to be 3x faster than standard capacity-oriented object stores like AWS.

article thumbnail

Pure Storage Announces Breakthrough STAC-M3 Benchmark Testing Results for High-performance and Quantitative Trading

Pure Storage

Pure Storage Announces Breakthrough STAC-M3 Benchmark Testing Results for High-performance and Quantitative Trading by Pure Storage Blog In the fast-paced world of high-frequency and quantitative trading , every microsecond counts. 17 of 24 STAC-M3 Kanaga mean-response time benchmarks exhibited enhancements, such as a 1.3x-1.5x

article thumbnail

National Coding Week: Upskill Your Coding Knowledge with Pure Storage

Pure Storage

How to List 67 Billion Objects in 1 Bucket in Golang: Learn what it takes to list all keys in a single bucket with 67 billion objects and build a simple list benchmark program in Golang. It does so by replacing Boto3 with equivalent functionality written in a modern, compiled language. Learn how to optimize it after enumeration of data sets.

article thumbnail

SQreamDB on FlashBlade//S

Pure Storage

The workload chosen was TPCx-BB , aka “Big Bench,” due to the broad industry applicability, access to the data generation tool, and the ability to compare against pre-existing benchmarks run by SQream on other platforms. The full TPCx-BB benchmark will not be tested as the environment is not set up to do so.