Michael Dell, end-to-end, PC to the Data Center

Michael Dell gave a keynote at Oracle OpenWorld, and there is blog post summarizing his presentation.

Michael emphasizes they go embrace the PC.

2. We Still Love Hardware: Without mentioning Hewlett-Packard by name, Dell took a few shots at HP’s potential PC division spin-out. Dell said his company has rapidly evolved from PCs to servers to cloud solutions.

“There are many reasons to stay committed to the PC, he said. “There will be two billion PCs in a few years.” Dell estimated that 95 percent of disk drives are in PCs, and five percent are in servers. A company without PCs can’t gain volume pricing advantages for server components, Dell asserted. “The client offers enormous scale,” said Dell. “Give up that scale and you need to raise your prices.”

Data Center is not specifically mentioned, but implied in this statement.

3. Total Picture: “Dell is not a PC company,” he said. “Dell is an end-to-end solutions company, and we understand the endpoint is a huge part of the solution. We are more than just hardware.”

Since it was Oracle's event, there is the Oracle statement.

6. The Dell-Oracle Relationship: JP Sarkis, VP of packaged applications for Dell Services, joined Dell on stage. Sarkis said Dell had been spending 70 percent of its IT budget on maintenance on 30 percent on innovation. More recently, 52 percent of Dell’s IT budget focuses on innovation, with 48 percent focused on maintenance. What drove the shift? Standardized business processes that leverage Oracle on Dell, plus a service oriented architecture (SOA), Sarkis claimed.

Servers are mentioned of course.

7. Dell PowerEdge Servers: Dell said his company is preparing the 12th generation of its PowerEdge servers. Dell asserted that the company will continue to offer the most comprehensive family of x86 servers. Dell said the PowerEdge systems will benefit from the little-watched acquisition of RNA Networks.

The last point that RNA Networks is a little-watched acquisition that I happen to visit 2 years ago and wrote this post.

So why not virtualize memory across multiple servers?

While in Portland I was able to visit with RNAnetworks and discuss their latest announcement.

RNA networks Brings Memory Virtualization Into the Enterprise Data Center

RNA Memory Virtualization Transforms Memory into a Shared, Networked Resource

Portland, Ore. – February 2, 2009 – RNA networks, a leader in memory virtualization software that transforms server memory into a shared network resource, today announced the launch of its Memory Virtualization Platform(MVP) and first product, RNAmessenger, based on the MVP.  Memory Virtualization unleashes high-performance computing from existing commodity hardware by decoupling memory from the processor and server.  Uniquely, the RNA Memory Virtualization Platform is transparent to existing applications and operating systems allowing enterprises to leverage their existing IT assets with no changes. 
“Reliance on fragmented local server memory has been a key roadblock to optimizing performance in data center clusters, but memory virtualization eliminates size limits and slashes access times by providing distributed shared memory for all CPUs in a cluster,” said Eyal Waldman, Chairman, President and CEO, Mellanox Technologies. “By combining RNA Networks' Memory Virtualization with Mellanox Technologies' unrivaled connectivity performance, data center architects can achieve new levels of performance with high efficiency and lower costs.”

The concept is simple.

RNA’s innovative Memory Virtualization Platform works by pooling or aggregating available memory across nodes, and making the memory pool available as a shared network resource available to all servers in the data center.  Servers can access the pool, contribute to it or both.


Where is the money savings? This is another problem I see with Cisco and VMware’s uber virtual data center solutions.  Where is the money savings?

I asked RNAnetworks CEO Clive Cook how much could be saved with memory Virtualization, and he said in grid computing type of scenarios where there is a high throughput requirement across multiple machines they have numbers below.

Bottom Line Economic Advantages

Performance Improvement 

Cost Savings

Fewer Load Balancers 

Less Aggregate Memory 

Storage Savings 

Power Savings 

Additional Benefits

  • Efficiency
  • Simplicity
  • Reliability
  • Resource Sharing
  • Low TCO
  • Consolidation