Intel lost 13 percentage points over 3 years in a high-growth workload type: memory-optimized workloads.
AUSTIN, Texas, April 4, 2023 /PRNewswire/ --Liftr Insights, a pioneer in market intelligence driven by unique data, shows that Intel lost 13 percentage points over the three-year period ended December 2022 within the memory-optimized workload category.
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Cloud providers identify ideal workloads for their different configurations. Standard workload groups include compute-optimized, storage-optimized, high-performance, accelerated, general purpose, and memory-optimized. Among all these types, memory-optimized has been the largest area of growth according to Liftr Insights data. Examples of specific workload types within memory-optimized include data mining, distributed file system, real-time analytics, and SAP HANA. Memory-optimized configurations increased 332% over the three-year period ended December 2022. The next closest workload increased 245%.
"The overall growth of the cloud and semiconductor space has hidden the internal dynamics," says Tab Schadt, CEO of Liftr Insights. "Intel and AMD can each show quarter-to-quarter growth while still losing market share. AMD has made a notable cut in that share of the overall market, but both Intel and AMD have been affected by growth of ARM."
Expansion of ARM-based processors, such as AWS Graviton (used by Amazon) and Ampere Computing (used by the other major cloud providers), accelerated over the past few years. Their growth has eroded the share Intel might otherwise have made in this space. Both ARM and Ampere Computing are IPO candidates in large part because of this disruption.
"What we see in the memory-optimized workloads is one of many signals derived from Liftr data," says Schadt.
Changes in workloads is one type of signal. Signals also come from changes in specific generations of processor, shifts in which brands are dominating the newer regions, and tracking which brands dominate recent deployments.
"This isn't just about Intel losing share. We see changes affecting AMD and ARM on the processor side and more changes on the accelerator side," says Schadt. "Objective data is a critical part for market intelligence analysts making informed investment decisions."
About Liftr Insights
Liftr Insights generates reliable market intelligence using unique data, including details about configurations, components, deployment geo, and pricing for:
- Server processors: Intel Xeon, AMD EPYC, and AWS's Arm-based Graviton brands
- Datacenter compute accelerators: GPUs, FPGAs, TPUs, and AI chips from NVIDIA, Xilinx, Intel, AMD, AWS, and Google
As shown on the Liftr Cloud Regions Map at https://bit.ly/LiftrCloudRegionsMap, among the companies tracked are Amazon Web Services,Microsoft Azure,Alibaba Cloud,Google Cloud, Oracle Cloud,and Tencent Cloudas well as semiconductor vendors AMD, Ampere,Intel, NVIDIA, and Xilinx. Liftr Insights subject matter experts translate company-specific service provider data into actionable alternative data.Market intelligence consumers can easily ingest this timely,standardized,andoperationally-compliant information into their predictive financial models.
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SOURCE Liftr Insights
