There are many different types of SSDs (solid-state drives) on the market, but not all are created equal when it comes to deep learning. In this article, we’ll take a look at the best SSD for deep learning and data science so that you can make an informed decision when it comes to choosing the right storage for your needs.
Why Should Use SSD For Deep Learning or Machine Learning?
Artificial intelligence (AI) and machine learning (ML) use cases have multiplied over the past several years, regardless of whether you run a huge corporation with a multimillion-dollar data center or a tiny business with a few application servers in a server closet. The performance of NVMe SSDs has shown to be superior for these workloads.
Data center leaders have become more astute and efficient in how their IT infrastructure handles these highly transactional workloads in today’s hybrid environment. They utilize high-performance object storage infrastructures with data-hungry, next-generation applications running on NVMe SSDs to capture, store quickly, and analyze more data for users.
Therefore, designing a PC with the finest SSDs for Deep Learning computers has come. For your deep learning, machine learning (ML), and data science projects, we have examined more than a hundred hard drives and selected what we believe to be the top SSDs for every price range.
SSD vs. HDD: Which Is Better For Deep Learning?
Our first stop is to talk about memory requirements for your entire workstation. When it comes to any kind of AI project, there will be a lot of data moving as you train your programs.
The various machine learning memory requirements are fairly complicated, but the idea of using SSD or HDD for machine learning is easy to tackle. As with most builds, it is probably best to have a bit of both.
For example: If you read your data from the drive as needed (blocking wait), then a 100 MB/s hard drive will take you about 185 milliseconds for an ImageNet 32 mini-batch! However, suppose you asynchronously “fetch” (async) the data before it is used (e.g., torch vision loaders). In that case, you will load the mini-batch in 185 milliseconds, while the computation time for most deep neural networks on ImageNet is about 200 milliseconds. Therefore, you won’t face any performance damage since you load the next mini-batch while the current one is still processing.
There will be plenty of temporary data storage, and it will be incredibly convenient to have an SSD to migrate data as needed quickly. However, for data that won’t be moved frequently or will eventually land in a permanent storage situation, HDD will work just fine and be far cheaper.
If you are not using large datasets and instead plan on using simulations to train your AI program, then you may be able to bypass the need for a permanent storage solution like an HDD to save on expenses. So we recommend SSDs for comfort and greater productivity: Programs start and respond faster and pre-process large files a little faster. If you buy an NVMe SSD, you will get an even smoother experience than a regular SSD. Therefore, the ideal configuration is to have a large and slow hard drive for datasets and an SSD for performance and comfort.
If you want to know more about the differences between SSD and HDD for machine learning, we have a great blog post that better explores these differences.
Today’s Best SSD For Deep Learning Lists
Samsung 980 SSD 1TB
|1||SAMSUNG 980 SSD 1TB PCle...||16,062 Reviews||$89 $69||View on Amazon|
|Samsung 980 Specifications|
|Interface/Form Factor||x4 PCIe 3.0/NVMe/M.2 2280|
|Sequential Read||3,500 MB/s|
|Sequential Write||3,000 MB/s|
|4KB Random Read||500,000 IOPS|
|4KB Random Write||480,000 IOPS|
|Bus Type||PCIe 4.0 x4 NVMe 1.4|
|NAND Type||Samsung 128L 3D TLC|
|Power Consumption||5.3 W Max|
- Competitive performance
- Large, fast-recovering dynamic SLC cache
- Attractive design
- AES 256-bit hardware encryption
- Software package
- 980 Pro-like endurance and 5-year warranty
- Slow write speeds after the SLC cache fills
An entry-level NVMe SSD with TLC NAND and a DRAMless controller is the SSD 980. It represents a brand-new product category for Samsung in the retail industry that it has never created before. This form of drive, with TLC and without DRAM, is already widely available on the market from other turn-key solution providers. This type of drive has been well-liked by OEMs since it enables them to advertise an NVMe SSD without paying the price of a high-end drive.
The “Pablo” controller serves as the foundation of the Samsung SSD 980. Although it has been available in the Samsung Portable SSD T7 family for more than a year, this isn’t a brand-new NVMe controller. This controller lacks a DRAM interface and has four NAND channels instead of the eight in Samsung’s high-end NVMe drives. The Pablo controller can saturate a PCIe 3.0 x4 host interface without using eight NAND channels because of the high NAND IO speeds allowed by current generations of 3D NAND.
Crucial MX500 2TB 3D NAND
|1||Crucial MX500 2TB 3D NAND SATA...||83,825 Reviews||$199 $118||View on Amazon|
|Crucial MX500 Specifications|
|Interface||6 Gbps SATA|
|Form Factor||2.5″ and M.2 2280|
|Controller||Silicon Motion SM2258|
|NAND||Micron 256Gb 64-layer 3D TLC|
|Sequential Read||560 MB/s|
|Sequential Write||510 MB/s|
|4KB Random Read||95,000 IOPS|
|4KB Random Write||90,000 IOPS|
- Very affordable
- Competitive performance
- Available in 2.5-inch or M.2 SATA versions
- Endurance rating low for usage cases involving heavy data writes
For several years, the MX500 served as Crucial’s premier SATA option, and the cost has decreased significantly throughout that time. However, the MX offers a completely different construction from the BX500 series, beginning with a Silicon Motion 2258 and a sizable DRAM cache.
The MX500 is combined with Micron’s 64 Layer TLC NAND. However, the 2TB storage is provided by a significantly larger 512Gbit die. This is backed by a 1.8 million-hour MTBF and 700 TBW endurance rating. The MX500, like many contemporary SATA systems, reaches the peak of the 6Gbps mountain at 560 MB/s read and 510 MB/s write. 95K read and 90K write are the ratings for random performance.
The MX500 contains several essential features that Crucial has included to boost performance. The most prominent is dynamic write acceleration, which uses an SLC buffer like many drives but can grow or decrease depending on drive status rather than having a fixed size.
SK Hynix Gold P31
|1||SK hynix Gold P31 1TB PCIe...||8,511 Reviews||$134 $107||View on Amazon|
|SK Hynix Gold P31 Specifications|
|Form Factor||M.2 2280 S3|
|Interface / Protocol||PCIe 3.0 x4 / NVMe 1.3|
|Controller||SK hynix Cepheus|
|Memory||SK hynix 128L TLC|
|Sequential Read||3,500 MBps|
|Sequential Write||3,200 MBps|
|Random Read||570,000 IOPS|
|Random Write||600,000 IOPS|
|Security||AES 256-bit encryption|
|Endurance (TBW)||750 TB|
- Class-leading power efficiency
- Top-tier performance
- Competitive endurance & 5-year warranty
- Single sided-form factor
- Low cost
- AES 256-bit encryption
- The 2TB model is a little slower than the 1TB model
- Black PCB only for 2TB capacity
The Gold P31 SSD from SK Hynix claims to be the first retail SSD to use 128-Layer flash, giving it a competitive advantage. The Gold P31 debuts on the market at a very low price due to the high bit density of SK Hynix’s most recent flash. The Gold P31 is an excellent value that will cause you to reconsider spending the additional $25 to $50 on the Samsung 970 EVO Plus. It is listed at comparable prices.
If you want to upgrade the storage on your laptop, the Gold P31 from SK Hynix is fantastic because it increases both capacity and battery life. Benchmarking tests may show that certain drives outperform the Gold P31, but the SK Hynix is far more power-efficient, allowing longer off-the-charger periods. The new SK Hynix Gold P31 should unquestionably be at the top of the list for laptop consumers who value battery life. Additionally, the Gold P31 is a well-rounded option for many desktop users because of its powerful write performance and outstanding efficiency.
Sabrent Rocket Q4 NVMe PCIe 4.0 2TB
|1||SABRENT 2TB Rocket Q4 NVMe...||1,264 Reviews||$219 $149||View on Amazon|
|Rocket Q4 2TB Specifications|
|Form Factor||M.2 2280|
|Interface / Protocol||PCIe 4.0 x4 / NVMe 1.3|
|Memory||Micron 96L QLC|
|Sequential Read||4,800 MBps|
|Sequential Write||3,600 MBps|
|Random Read||350,000 IOPS|
|Random Write||700,000 IOPS|
|Endurance (TBW)||400 TB|
|Warranty||5-Years w/ Registration; 1-Year w/out|
- Capacity up to 4TB
- High performance and efficiency
- Up to 5-years warranty
- 1-year warranty without registration
- Slow write speed after write cache fills
- Low endurance-per-GB compared to TLC
Sabrent’s Rocket Q4 might be just what consumers of deep learning are searching for with its stylish design and affordable price. This M.2 NVMe SSD can deliver up to 4.9GBps while remaining cool to the touch, but it is neither the quickest nor the toughest SSD on the market. Its price-to-performance ratio becomes crucial at that point.
One of the first QLC-based SSDs with a high-end Gen3 NVMe controller to hit the market was Sabrent’s Rocket Q, and the company’s latest Rocket Q4 is one of the first. With Phison’s PS5016-E16 controlling up to 4TB of Micron’s 96-Layer QLC flash, Sabrent’s Rocket Q4 bridges the gap between the Rocket Q and Rocket NVMe 4.0 we previously examined by providing potential customers with speed, capacity, and affordability.
Samsung 970 EVO Plus 2TB
|1||Samsung 970 EVO Plus SSD 2TB...||46,739 Reviews||$499 $129||View on Amazon|
|Samsung 970 EVO Plus Specifications|
|Form factor||M.2 2280|
|Capacity||From 250GB to 2TB|
|Interface||PCIe 3.0 x4|
|Reading speed||3,500 MB / s|
|Write speed||3,300 MB / s|
|Random Read Speed||620,000 IOPS|
|Random Write Speed||560,000 IOPS|
|Particles (NAND Flash)||92L TLC V-NAND|
|NAND Flash Controller||Samsung Phoenix|
|NAND Flash Type||Samsung V-NAND (TLC)|
|Encryption||256-Bit AES (Hardware-Based)|
|Durability||From 150 TBW (250 GB) to 1200 TBW (2 TB)|
- Solid overall performance
- Black PCB
- Excellent software package
- Could use further efficiency optimization
With the Samsung 970 EVO Plus SSD, you need to wait the time for the content, which will be reduced. The NVMe interface on this system provides more bandwidth, less latency, and efficient power use. You can experience seamless boot-ups with speeds of up to 3,500MB s and 3,300MB, respectively.
Prepare for a quick experience in the majority of data transfer performance areas. If that wasn’t enough, the 600000 IOPS Random Read will definitely make you smile. The most recent model in Samsung’s highly regarded and best-selling range of SSD storage is the 970 EVO Plus.
It offers an NVMe M/N interface, which is ideal for content creators, professional gamers, and tech enthusiasts. You should all look at this beauty if you’re trying to maximize 4K & 3D performance. Sequential read speeds can reach 3500MB/s, roughly 4 times quicker than SATA drives.
Their Dynamic Thermal Guard monitoring is always available for customers that require the highest level of dependability from their data storage system. Performance declines can be prevented by maintaining ideal operating temperatures. Effortless performance? Check files not being moved to any other media format. Double-check. Efficient self-optimization? The new method for guaranteeing the security of your data is the Samsung 970 EVO Plus SSD. The Samsung V-NAND Technology used by the 970 EVO Plus SSD provides increased bandwidth. The Dynamic Thermal Guard prevents performance decreases.
|1||Crucial P5 Plus 2TB PCIe Gen4...||7,595 Reviews||$319 $136||View on Amazon|
|Crucial P5 Specifications|
|Form Factor||M.2 2280 SSD|
|Interface||PCIe Gen 3.0 x4, NVMe|
|Dimensions||M.2 2280 Standard|
|NAND Type||3 Bit TLC|
|Sequential Read||3.400 MB/s|
|Sequential Write||3.000 MB/s|
|Reliability (MTTF)||1,8 million hours|
|Warranty||5 years limited|
- Competitive pricing
- Hardware-based AES 256-bit encryption
- Blacked-out aesthetics
- 5-year warranty
- Software suite
- Runs hot
- Not quite as performant as SK Hynix or Samsung
Although Micron’s six-core NVMe controller and some of the most recent 96L TLC flash are used in Crucial’s P5, a mainstream PCIe 3.0 x4 M.2 NVMe SSD, the company ultimately relies on its value to persuade customers to buy it. The P5 still performs admirably for what it is, even though it isn’t as quick as the newest Gen4 SSDs on the market and can become rather warm under heavy loads.
The P5 from Crucial has a blacked-out design, can achieve sequential read and write speeds of up to 3.4/3 GBps, and has a small, single-sided M.2 form factor for wide compatibility. Additionally, it has an average endurance rating, a standard 5-year guarantee, and some value-added software as a bonus. It even has OPAL-compliant hardware-accelerated AES 256-bit encryption. The best part is that it has recently become even more reasonably priced than before. The Crucial P5 is priced to sell at a very low cost, making it a good deal for those hoping to save a few dollars over the very finest SSDs, whether you’re a gamer, prosumer, or PC user searching for a storage upgrade for deep learning.
WD Red SN700
|1||Western Digital 1TB WD Red...||153 Reviews||$144 $108||View on Amazon|
|WD Red SN700 Specifications|
|Form Factor||M.2 2280|
|Interface / Protocol||PCIe 3.0 x4 / NVMe 1.3|
|Controller||WD NVMe Architecture|
|Memory||Kioxia BiCS4 96L TLC|
|Sequential Read||3,400 MBps|
|Sequential Write||2,900 MBps|
|Random Read||480,000 IOPS|
|Random Write||540,000 IOPS|
|Endurance (TBW)||2,500 TB|
- High capacity options
- Strong sustained performance
- Middling general performance
- Unexciting, old technology
- No power loss protection
The Red SN700 can have sequential read/write rates of up to 3.4/3.1 GBps and random read/write speeds of up to 550,000/520,000 IOPS. The drive costs $0.12 to $0.26 per gigabyte and comes in 256GB, 512GB, 1TB, 2TB, and 4TB sizes. Because it’s a NAS drive, it’s targeted at bigger capacities where the price per gigabyte is extremely cheaper, especially at 4TB, which can be challenging to obtain with reasonable pricing with TLC flash. If someone needs this mix of cost, performance, and endurance, it becomes an even more tempting alternative for consumer use.
The five-year warranty comes with 1PBW per TB capacity up to and including the 1TB SKU, with 2.5PBW and 5.1PBW total for the 2TB and 4TB SKUs, respectively. The drive offers typical working circumstances and characteristics. However, this has greater endurance than WD’s consumer variations (for example, a 70C maximum operating temperature). Unfortunately, the SN700 lacks power loss protection, which, while expected, lessens its usefulness in situations needing the highest level of reliability.
Samsung 870 EVO
|1||SAMSUNG 870 EVO SATA III SSD...||26,213 Reviews||$89 $64||View on Amazon|
|Samsung 860 EVO Specifications|
|Interface||6 Gbps SATA|
|Form Factor||2.5″, mSATA, M.2 2280|
|NAND||Samsung V-NAND 3bit MLC (TLC)|
|Sequential Read||560 MB/s|
|Sequential Write (SLC Cache)||520 MB/s|
|Sequential Write (TLC)||500 MB/s|
|4KB Random Read||100k IOPS|
|4KB Random Write||90k IOPS|
- Reliable and responsive architecture
- Appealing aesthetics
- AES 256-bit encryption
- Capacities up to 4TB
- 5-year warranty
- Software suite
- Premium price
The company’s own 860 EVO, the best-selling SATA SSD on the market, is being replaced by Samsung’s 870 EVO, which has large shoes to fill. Samsung’s SSDs have developed quite a following and reputation over the years thanks to their outstanding performance and efficiency, large capacities, and excellent reliability ratings.
With its most recent 6th-gen 128-Layer V-NAND TLC flash and upgraded MKX ‘Metis’ SATA 6Gbps controller, Samsung’s 870 EVO is the most sophisticated model yet. The new SSD is still constrained by the SATA interface and cannot compete with the most recent NVMe SSDs. Nevertheless, according to Samsung, the 870 EVO has up to 38% more performance than its predecessor for common computing activities, and the 250GB variant has up to 30% more sustained write performance.
Deep Learning and Machine Learning Memory Requirements
Building a machine learning workstation can be difficult, not to mention choosing the right workstation with the proper machine learning memory requirements. There are a lot of moving parts based on the types of projects you plan to run.
Understanding machine learning memory requirements is a critical part of the building process. Sometimes, though, it is easy to overlook. The average memory requirement is 16GB of RAM, but some applications require more memory.
A massive GPU is typically understood to be a “must-have”, but thinking through the machine learning memory requirements probably doesn’t weigh into that purchase. However, it can make or break your application performance.
Best SSD for Machine Learning Buying Guide
Considering these aspects, switching to SSDs will provide you with many amazing advantages. A solid-state drive is a newer, faster, easier method of securing your data. Additionally, transfer rates are noticeably higher while moving larger files.
When you have sequential read or write rates of up to 3500MB/s and 3300MB/s, you have a higher chance of winning. Your performance will greatly improve as a result of this.
Purchasing an SSD is primarily about storage. Along with other helpful features, you need 2 TB of space. To keep all of your files organized and secure in one location, you must have this capability.
You can find a secure location for your data using AES 256-bit encryption. Your solid-state drive’s inclusion of such a function gives you the highest level of protection against data loss due to hackers and thieves.
Purchasing a guarantee of a maximum of five years prevents the trouble of damage and repair. Knowing that your brand has your back will let you rest easy. Additionally, it places faith in the ability of the maker to develop beneficial products and enhancements throughout time.
The ideal temperature is automatically maintained inside by thermal protectors. This feature reduces the performance hit by slowing down the speed of your SSD. Through the use of this specification, any additional heat generated by GPU pushing or fluctuation will be automatically regulated.
An excellent SSD management solution can be achieved with Magician software, which can copy files and perform transfers. You can easily recover lost data if you have a powerful device like an SSD.
How Much Is RAM Needed For Deep Learning?
A general rule of thumb for RAM for deep learning is to have at least as much RAM as you have GPU memory and then add about 25% for growth. This simple formula will help you stay on top of your RAM needs and will save you a lot of time switching from SSD to HDD if you have both set up.
While there isn’t a preferred overarching amount of RAM necessary for deep learning projects, this is an easy way to stay ahead of any issues and have to worry about scaling in the immediate future. Depending on if you are using a data-intensive visual component for training your deep learning program, though, you may need more than you think.
How much SSD do I need for deep learning?
You should be looking for a RAM range of 8GB to 16GB, more preferably 16 GM of RAM. Try to purchase an SSD of size 256 GB to 512 GB for installing the operating system and storing some crucial projects, and an HDD space of 1TB to 2TB for storing deep learning projects and their datasets. If you don’t mind the budget, you can buy an MVNE SSD with high capacity to respond to your needs.
How much VRAM is needed for deep learning?
Deep Learning requires a high-performance workstation to handle high processing demands adequately. Your system should meet or exceed the following requirements before you start working with Deep Learning: Dedicated NVIDIA GPU graphics card with CUDA Compute Capability 3.5 or higher and at least 6 GB of VRAM.
We hope you found this blog to be helpful in learning about the best SSD for your deep learning computer and whether you should consider SSD or HDD for machine learning. Please comment below if you have found some different ideals better for your own situation, or if you have any questions please feel free to contact us today.
Otherwise, you can browse other articles on the Memoright blog. Keep a lookout for more helpful articles on the way soon!