Architecture Benchmark Capacity 
Pure Storage
JANUARY 18, 2024
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
Pure Storage
NOVEMBER 18, 2024
To achieve all of this, an AI-ready infrastructure that has been tested, benchmarked, and validated by industry leaders gives enterprises confidence that what they’re building will support their AI-powered business requirements immediately and in the future. The Pure Storage Platform A platform that grows with you, forever. All as-a-service.
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Pure Storage
SEPTEMBER 20, 2024
A Long-term Consistent Vision for a Storage-as-a-service Platform Over a decade ago, Pure Storage took a bold, visionary path while others in the storage industry were busy patchworking more systems together and architectures. It delivers benchmark scores and best practices to align with NIST 2.0 The result?
Pure Storage
NOVEMBER 9, 2023
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.
Pure Storage
JUNE 19, 2024
Simplicity Delivered through a True Services Experience Imagine a world where a storage administrator can deliver storage based solely on capacity, protocol, and performance. Evergreen//One, Optimized for AI Projecting future storage capacity needs for AI workloads can be nearly impossible. There’s a better way.
Pure Storage
MAY 2, 2024
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.
Pure Storage
MAY 2, 2024
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.
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