Skip to main content

Research: AMD more efficient than Intel

The tests were performed on servers configured with 2, 4, 6 and 8 gigabytes of main memory at various transaction processing load levels. The results show that for certain configurations and at certain load levels the Intel Xeon based server was 2.4 to 11.7 percent more power efficient while in other cases the AMD Opteron based server was 9.2 to 23.1 percent more power efficient. In addition, when the systems were idle and waiting for transactions to process, the AMD server was 30.4 to 53.1 percent more power efficient.

Power consumption while the servers are idle is particularly significant since many servers spend most of their time waiting for work. A November 16, 2006 press release(1) from IBM quotes a report by the Robert Frances Group(2) which states that on average servers in datacenters are idle 80 to 85 percent of the time.

Other observations that can be made from the test results include: 1) Larger memory configurations deliver both higher throughput and better power efficiency, 2) Intel's power efficiency advantages decrease as memory size increases, 3) AMD's power efficiency advantages increase as memory size increases, 4) For primarily calculation type workloads, the Xeon delivers 8.0 to 14.0 percent higher peak throughput, and 5) For primarily disk I/O intensive workloads the Opteron delivers 11.3 to 19.4 percent higher peak throughput.

These test results were collected by Neal Nelson's second generation Server Power Efficiency Benchmark. This test is a client server benchmark where world wide web transactions are processed against a server configured with Novell's SUSE Linux Enterprise Server, the Apache2 web server software and the MySQL relational database. The benchmark subjects a server to various user loads, reports the power consumed at each load level and provides meaningful comparisons of server power usage.


Read Neal Nelson benchmark Lab's news article and here's the full PDF report.

Comments

Popular posts from this blog

Get Vyatta Virtual Appliance, now VMware certified!

We all know Vyatta, don't we?

Vyatta, the leader in Linux-based networking, today announced that its open-source networking software has received VMware Virtual Appliance Certification, thereby providing customers with a solution that has been optimized for a production-ready VMware environment. The company also announced it has joined the VMware Technology Alliance Partner (TAP) Program. As a member of TAP, Vyatta will offer its solutions via the TAP program website. With the Vyatta virtual appliance for VMware environments, organizations can now include Vyatta’s router, firewall and VPN functions as part of their virtualized infrastructure.

Vyatta combines enterprise-class routing and security capabilities into an integrated, reliable and commercially supported software solution, delivering twice the performance of proprietary network solutions at half the price. Running Vyatta software as virtual appliances gives customers many more options for scaling their data centers and cons…

3PAR adds native LDAP support to simplify administration

3PAR®, the leading global provider of utility storage, announced today native support for lightweight directory access protocol (LDAP). Support for LDAP enables centralized user authentication and authorization using a standard protocol for managing access to IT resources. With 3PAR’s support for LDAP, customers are able to now integrate 3PAR Utility Storage--a simple, cost-efficient, and massively scalable storage platform—with standard, open enterprise directory services. The result is simplified security administration with centralized access control and identity management.

“3PAR Utility Storage already provides us with a reliable, shared, and easy-to-use consolidated storage platform,” said Burzin Engineer, Vice President of Infrastructure Services at Shopzilla. "Now, with 3PAR support for LDAP, managing security commonly--across all our resources, including storage--is also simple and efficient.”

Press Release

DeepLearningTrucker Part 1