Mellanox Technologies Archives

Storage IO straight to GPU

By cfheoh | July 5, 2021 - 9:00 am |July 3, 2021 100Gigabit Ethernet, Algorithm, Analytics, API, Artificial Intelligence, Composable Infrastructure, compression, CXL, Deduplication, Deep Learning, Filesystems, High Performance Computing, Hyperconvergence, Machine Learning, Mellanox, Mellanox Technologies, Microsoft, nVidia, NVMe, RDMA, Vast Data, WekaIO

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The parallel processing power of the GPU (Graphics Processing Unit) cannot be denied. One year ago, nVidia® overtook Intel® in market capitalization. And today, they have doubled their market cap lead over Intel®, [as of July 2, 2021] USD$510.53 billion vs USD$229.19 billion.

Thus it is not surprising that storage architectures are changing from the CPU-centric paradigm to take advantage of the burgeoning prowess of the GPU. And 2 announcements in the storage news in recent weeks have caught my attention – Windows 11 DirectStorage API and nVidia® Magnum IO GPUDirect® Storage.

nVidia GPU

Exciting the gamers

The Windows DirectStorage API feature is only available in Windows 11. It was announced as part of the Xbox® Velocity Architecture last year to take advantage of the high I/O capability of modern day NVMe SSDs. DirectStorage-enabled applications and games have several technologies such as D3D Direct3D decompression/compression algorithm designed for the GPU, and SFS Sampler Feedback Streaming that uses the previous rendered frame results to decide which higher resolution texture frames to be loaded into memory of the GPU and rendered for the real-time gaming experience.

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Is Software Defined right for Storage?

By cfheoh | April 19, 2021 - 9:00 am |April 18, 2021 Acquisition, API, Appliance, ATA over Ethernet, Ceph, Composable Infrastructure, Coraid, Cray Inc, Data Direct Networks, deduplication, Deduplication, Filesystems, FreeNAS, Gluster, HDS, High Performance Computing, HPE Simplivity, Hyperconvergence, Infiniband, Intel, iXsystems, Liqid, Mellanox Technologies, Minio, NetApp, Nexenta, Nutanix, nVidia, OpenIO, Openstack, Oracle, PCIe, Performance Benchmark, Performance Caching, Pure Storage, RAID, RDMA, Redhat, Simplivity, SNIA, SoftIron, Software Defined Storage, Solaris, Solid State Devices, Storage Optimization, TrueNAS, Vast Data, Virtualization

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George Herbert Leigh Mallory, mountaineer extraordinaire, was once asked “Why did you want to climb Mount Everest?“, in which he replied “Because it’s there“. That retort demonstrated the indomitable human spirit and probably exemplified best the relationship between the human being’s desire to conquer the physical limits of nature. The software of humanity versus the hardware of the planet Earth.

Juxtaposing, similarities can be said between software and hardware in computer systems, in storage technology per se. In it, there are a few schools of thoughts when it comes to delivering storage services with the notable ones being the storage appliance model and the software-defined storage model.

There are arguments, of course. Some are genuinely partisan but many a times, these arguments come in the form of the flavour of the moment. I have experienced in my past companies touting the storage appliance model very strongly in the beginning, and only to be switching to a “software company” chorus years after that. That was what I meant about the “flavour of the moment”.

Software Defined Storage

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The Edge is coming! The Edge is coming!

By cfheoh | October 12, 2020 - 9:15 am |October 11, 2020 100Gigabit Ethernet, Analytics, Big Data, Containers, Data, Deep Learning, Edge Computing, Flash, Industry 4.0, InfluxDB, Linux, Machine Learning, Mellanox, Mellanox Technologies, Minio, nVidia, NVMe, Pravega, SNIA, Solid State Devices

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Actually, Edge Computing is already here. It has been here on everyone’s lips for quite some time, but for me and for many others, Edge Computing is still a hodgepodge of many things. The proliferation of devices, IoT, sensor, end points being pulled into the ubiquitous term of Edge Computing has made the scope ever changing, and difficult to pin down. And it is this proliferation of edge devices that will generate voluminous amount of data. Obvious questions emerge:

How to do you store all the data?
How do you process all the data?
How do you derive competitive value from the data from these edge devices?
How do you securely transfer and share the data?

From the storage technology perspective, it might be easier to observe what are the traits of the data generated on the edge device. In this blog, we also observe what could some new storage technologies out there that could be part of the Edge Computing present and future.

Edge Computing overview – Cloud to Edge to Endpoint

Storage at the Edge

The mantra of putting compute as close to the data and processing it where it is stored is the main crux right now, at least where storage of the data is concerned. The latency to the computing resources on the cloud and back to the edge devices will not be conducive, and in many older settings, these edge devices in factory may not be even network enabled. In my last encounter several years ago, there were more than 40 interfaces, specifications and protocols, most of them proprietary, for the edge devices. And there is no industry wide standard for these edge devices too.

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Dell EMC Isilon is an Emmy winner!

By cfheoh | March 16, 2020 - 7:41 am |March 17, 2020 100Gigabit Ethernet, Acquisition, Analytics, Appliance, CIFS, Cloud, Clusters, Containers, Data Availability, Deduplication, deduplication, Deep Learning, Dell, DellEMC, Disks, EMC, Flash, Gartner, High Performance Computing, Isilon, Mellanox, Mellanox Technologies, NAS, NetApp, NFS, Performance Caching, Pure Storage, Qumulo, Scale-out architecture, SMB, Snapshots, Software Defined Storage, Solid State Devices, Storage Field Day, Storage Market Share, Storage Optimization, Storage Tiering, Tech Field Day, WekaIO

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[ Disclosure: I was invited by GestaltIT as a delegate to their Storage Field Day 19 event from Jan 22-24, 2020 in the Silicon Valley USA. My expenses, travel, accommodation and conference fees were covered by GestaltIT, the organizer and I was not obligated to blog or promote the vendors’ technologies presented at this event. The content of this blog is of my own opinions and views ]

And the Emmy® goes to …

Yes, the Emmy® goes to Dell EMC Isilon! It was indeed a well deserved accolade and an honour!

Dell EMC Isilon had just won the Technology & Engineering Emmy® Awards a week before Storage Field Day 19, for their outstanding pioneering work on the NAS platform tiering technology of media and broadcasting content according to business value.

A lasting true clustered NAS

This is not a blog to praise Isilon but one that instill respect to a real true clustered, scale-out file system. I have known of OneFS for a long time, but never really took the opportunity to really put my hands on it since 2006 (there is a story). So here is a look at history …

Back in early to mid-2000, there was a lot of talks about large scale NAS. There were several players in the nascent scaling NAS market. NetApp was the filer king, with several competitors such as Polyserve, Ibrix, Spinnaker, Panasas and the young upstart Isilon. There were also Procom, BlueArc and NetApp’s predecessor Auspex. By the second half of the 2000 decade, the market consolidated and most of these NAS players were acquired.

NetApp acquired Spinnaker in 2003
Part of Auspex was acquired by NetApp in 2003; The other by Glasshouse Technologies
Procom was picked up by Sun Microsystems in 2005
Polyserve went to HP in 2007
Ibrix joined HP as well in 2009
Isilon got acquired by EMC in 2010
BlueArc gobbled up by HDS in 2011

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Is General Purpose Object Storage disenfranchised?

By cfheoh | December 23, 2019 - 5:40 pm |January 14, 2020 100Gigabit Ethernet, Amazon Web Services, Analytics, API, Artificial Intelligence, Big Data, BYOD, Ceph, Cloud, Cloudian, Clusters, Deep Learning, DellEMC, Docker, Dropbox, Edge Computing, Filesystems, Flash, Gartner, Hadoop, HDS, High Performance Computing, Hitachi Vantara, IDC, Industry 4.0, IoT, Lustre, Machine Learning, Mellanox Technologies, Minio, NetApp, Object Storage, OpenIO, Openstack, Performance Benchmark, Reliability, Scale-out architecture, Software Defined Storage, Storage Field Day, Storage Market Share, swiftstack, Tape storage, Tech Field Day

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[Disclosure: I am invited by GestaltIT as a delegate to their Storage Field Day 19 event from Jan 22-24, 2020 in the Silicon Valley USA. My expenses, travel, accommodation and conference fees will be covered by GestaltIT, the organizer and I am not obligated to blog or promote the vendors’ technologies to be presented at this event. The content of this blog is of my own opinions and views]

This is NOT an advertisement for coloured balls.

This is the license to brag for the vendors in the next 2 weeks or so, as we approach the 2020 new year. This, of course, is the latest 2019 IDC Marketscape for Object-based Storage, released last week.

My object storage mentions

I have written extensively about Object Storage since 2011. With different angles and perspectives, here are some of them:

The Future is Intelligent Objects (2011)
What should be Cloud Storage? (2011)
APIs that stick in Storage (2012)
Has Object Storage become the Everything Store? (2013)
Of Object Storage, Filesystems and Multicloud (2017)
My Dilemma of Stateful Storage Marriage (2018)
The Malaysian Openstack Storage Conundrum (2018)
Sleepless in Malaysia with Object Storage (2019)
The Waning Light of Openstack Swift (2019)

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Storage Performance Considerations for AI Data Paths

By cfheoh | June 17, 2019 - 10:50 am |June 17, 2019 100Gigabit Ethernet, Algorithm, Analytics, API, Artificial Intelligence, Big Data, Cloud, Composable Infrastructure, Data, Data Fabric, Data Management, Data Privacy, Data Security, Digital Transformation, Drivescale, E8 Storage, Edge Computing, Elastifile, Excelero, Filesystems, High Performance Computing, Hyperconvergence, Industry 4.0, Infiniband, Intel, Liqid, Lustre, Machine Learning, Mellanox Technologies, NVMe, Object Storage, Performance Benchmark, Performance Caching, Quantum Corporation, RDMA, Software-defined Datacenter, Storage Optimization, Storage Tiering, ThinkParq, Vast Data, Virtualization, WekaIO

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The hype of Deep Learning (DL), Machine Learning (ML) and Artificial Intelligence (AI) has reached an unprecedented frenzy. Every infrastructure vendor from servers, to networking, to storage has a word to say or play about DL/ML/AI. This prompted me to explore this hyped ecosystem from a storage perspective, notably from a storage performance requirement point-of-view.

One question on my mind

There are plenty of questions on my mind. One stood out and that is related to storage performance requirements.

Reading and learning from one storage technology vendor to another, the context of everyone’s play against their competitors seems to be “They are archaic, they are legacy. Our architecture is built from ground up, modern, NVMe-enabled“. And there are more juxtaposing, but you get the picture – “We are better, no doubt“.

Are the data patterns and behaviours of AI different? How do they affect the storage design as the data moves through the workflow, the data paths and the lifecycle of the AI ecosystem?

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Lift and Shift Begone!

By cfheoh | April 25, 2019 - 5:30 pm |April 25, 2019 Amazon, Amazon Web Services, Cloud, Composable Infrastructure, Data Availability, Data Fabric, Data Management, High Performance Computing, Hyperconvergence, Mellanox Technologies, NetApp, NVMe, Server SAN, Software Defined Storage

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I am excited. New technologies are bringing the data (and storage) closer to processing and compute than ever before. I believe the “Lift and Shift” way would be a thing of the past … soon.

Data is heavy

Moving data across the network is painful. Moving data across distributed networks is even more painful. To compile the recent first image of a black hole, an amount of 5PB or more had to shipped for central processing. If this was moved over a 10 Gigabit network, it would have taken weeks.

Furthermore, data has dependencies. Snapshots, clones, and other data relationships with applications and processes render data inert, weighing it down like an anchor of a ship.

When I first started in the industry more than 25 years ago, Direct Attached Storage (DAS) was the dominating storage platform. I had a bulky Sun MultiDisk Pack connected via Fast SCSI to my SPARCstation 2 (diagram below):

Then I was assigned as the implementation engineer for Hock Hua Bank (now defunct) retail banking project in their Sibu HQ in East Malaysia. It was the first Sun SPARCstorage 1000 (photo below), running a direct attached Fibre Channel 0.25 Gbps FCAL (Fibre Channel Arbitrated Loop). It was the cusp of the birth of SAN (Storage Area Network).

Photo from https://www.cca.org/dave/tech/sys5/

The proliferation of SAN over the next 2 decades pushed DAS into obscurity, until SAS (Serial Attached SCSI) came about. Added to the mix was the prominence of Cloud Storage. But on-premises storage and Cloud Storage didn’t always come together. There was always a valley between the 2, until the public clouds gained a stronger foothold in the minds of IT and businesses. Today, both on-premises storage and cloud storage are slowly cosying as one Data Singularity, thanks to vision and conceptualization of data fabrics. NetApp was an early proponent of the Data Fabric concept 4 years ago. Continue reading →

WekaIO controls their performance destiny

By cfheoh | March 17, 2019 - 5:33 pm |March 17, 2019 Amazon Web Services, Analytics, Appliance, Big Data, CIFS, Cloud, Deep Learning, Filesystems, Flash, High Performance Computing, Infiniband, Linux, Lustre, Machine Learning, Mellanox Technologies, NAS, NetApp, NFS, NVMe, Object Storage, PCIe, Performance Benchmark, Performance Caching, RDMA, Scale-out architecture, SMB, Software Defined Storage, Storage Field Day, Storage Optimization, Storage Tiering, Tech Field Day, Virtualization, WekaIO, Western Digital

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[Preamble: I have been invited by GestaltIT as a delegate to their Tech Field Day for Storage Field Day 18 from Feb 27-Mar 1, 2019 in the Silicon Valley USA. My expenses, travel and accommodation were covered by GestaltIT, the organizer and I was not obligated to blog or promote their technologies presented at this event. The content of this blog is of my own opinions and views]

I was first introduced to WekaIO back in Storage Field Day 15. I did not blog about them back then, but I have followed their progress quite attentively throughout 2018. 2 Storage Field Days and a year later, they were back for Storage Field Day 18 with a new CTO, Andy Watson, and several performance benchmark records.

Blowout year

2018 was a blowout year for WekaIO. They have experienced over 400% growth, placed #1 in the Virtual Institute IO-500 10-node performance challenge, and also became #1 in the SPEC SFS 2014 performance and latency benchmark. (Note: This record was broken by NetApp a few days later but at a higher cost per client)

The Virtual Institute for I/O IO-500 10-node performance challenge was particularly interesting, because it pitted WekaIO against Oak Ridge National Lab (ORNL) Summit supercomputer, and WekaIO won. Details of the challenge were listed in Blocks and Files and WekaIO Matrix Filesystem became the fastest parallel file system in the world to date.

Control, control and control

I studied WekaIO’s architecture prior to this Field Day. And I spent quite a bit of time digesting and understanding their data paths, I/O paths and control paths, in particular, the diagram below:

Starting from the top right corner of the diagram, applications on the Linux client (running Weka Client software) and it presents to the Linux client as a POSIX-compliant file system. Through the network, the Linux client interacts with the WekaIO kernel-based VFS (virtual file system) driver which coordinates the Front End (grey box in upper right corner) to the Linux client. Other client-based protocols such as NFS, SMB, S3 and HDFS are also supported. The Front End then interacts with the NIC (which can be 10/100G Ethernet, Infiniband, and NVMeoF) through SR-IOV (single root IO virtualization), bypassing the Linux kernel for maximum throughput. This is with WekaIO’s own networking stack in user space. Continue reading →

Microsoft desires Mellanox

By cfheoh | December 20, 2018 - 11:02 am |December 20, 2018 100Gigabit Ethernet, Acquisition, Amazon, Artificial Intelligence, Cloud, Data Fabric, Data Management, Deep Learning, Edge Computing, High Performance Computing, Infiniband, Machine Learning, Mellanox Technologies, Microsoft, NVMe, Storage Field Day, Tech Field Day, Virtualization

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My lazy Thursday morning was spurred by a posting by Stephen Foskett, Chief Organizer of Tech Field Days. “Microsoft mulls the acquisition of Mellanox”

The AWS factor

A quick reaction leans towards a strange one. Microsoft of all people, buying a chip company? Does it make sense? However, leaning deeper, it starts to make some sense. And I believe the desire is spurred by Amazon Web Services announcement of their Graviton processor at AWS re:Invent last month.

AWS acquired Annapurna Labs in early 2015. From the sources, Annapurna was working on low powered, high performance networking chips for the mid-range market. The key words – lower powered, high performance, mid-range – are certainly the musical notes to the AWS opus. And that would mean the ability for AWS to control their destiny, even at the edge. Continue reading →

Category Archives: Mellanox Technologies