Scientific Computing is nowadays the “third pillar of science”, standing right next to theoretical analysis and experiments for scientific discovery.
Computation becomes crucially important in situations such as:
- The problem at hand cannot be solved by traditional experimental or theoretical means, such as attempting to predict climate change
- Experimentation may be dangerous, e.g., characterization of toxic materials
- The problem would be too expensive or time-consuming to try to solve by other avenues, e.g. determination of the structure of proteins
Furthermore, computer simulations can be embedded in optimization algorithms for optimal designs, e.g. the optimal design of aircraft in the computer instead of experience-driven trial and error designs with the support of expensive wind tunnel experiments.
Another characteristic of Scientific Computing is that it is a multidisciplinary activity. Generally, it involves experts in the application at hand, and also applied mathematicians and computer scientists that help to implement the computational solution.
But what is Scientific Computing?
The question is answered in [Golub&Ortega]* as follows:
Scientific Computing is the collection of tools, techniques, and theories required to solve on a computer mathematical models of problems in Science and Engineering.
A majority of these tools, techniques, and theories originally developed in Mathematics, many of them having their genesis long before the advent of electronic computers. This set of mathematical theories and techniques is called Numerical Analysis (or Numerical Mathematics) and constitutes a major part of scientific computing. The development of the electronic computer, however, signaled a new era in the approach to the solution of scientific problems. Many of the numerical methods that had been developed for the purpose of hand calculation (including the use of desk calculators for the actual arithmetic) had to be revised and sometimes abandoned. Considerations that were irrelevant or unimportant for hand calculation now became of utmost importance for the efficient and correct use of a large Computer System. Many of these considerations – programming languages, operating systems, management of large quantities of data, the correctness of programs – were subsumed under the new discipline of Computer Science, on which scientific computing now depends heavily. But mathematics itself continues to play a major role in scientific computing: it provides the language of the mathematical models that are to be solved and information about the suitability of a model (Does it have a solution? Is the solution unique?) and it provides the theoretical foundation for the numerical methods and, increasingly, many of the tools from computer science.
In summary, then, scientific computing draws on mathematics and computer science to develop the best way to use computer systems to solve problems from science and engineering.
Scientific Computing e requires a tremendous amount of processing power and RAM depending upon the complexity of your projects.
Here we will look at the best laptops for Scientific Computing
LIST OF 6 BEST LAPTOPS FOR SCIENTIFIC COMPUTING
- LENOVO THINKPAD X1 CARBON
- APPLE MACBOOK PRO
- DELL XPS 13/15
- HUAWEI MATEBOOK X PRO
- ACER SWIFT 3
- ASUS VIVOBOOK S
1. LENOVO THINKPAD X1 CARBON
Lenovo ThinkPads are known to have one of the best keyboards in the laptop market. They have the right tactile feedback and key travel.
As a data scientist, a typing session can be long and a good keyboard helps a lot. You are able to type much faster and feel more comfortable.
In addition, the 14-inch WQHD (2560 x 1440) IPS which is anti-glare. Nice viewing angles, color accuracy, and reproduction along with an anti-glare display make it easy on the eye.
Battery life is long about 10-11 hours of normal usage. Close to half a day.
The Lenovo ThinkPad X1 Carbon also goes strong in the performance department. It basically fulfills are the requirements to handle large datasets up to a point that is.
A decent amount of RAM and a 512 GB PCIe NVMe SSD large enough to store your data files and access data very fast. The port selection is balanced – two Thunderbolt 3 ports and two USB 3.1.
Because the Lenovo ThinkPad X1 Carbon is a high-end machine it comes with a hefty price tag. The speakers are not as great too.
The Lenovo ThinkPad is a solid laptop. It offers a lot in terms of its keyboard, battery life, portability, and performance. Reasons why it’s an expensive machine.
2. APPLE MACBOOK PRO
The Apple MacBook Pro is a pricey workstation. Apple Tax included. The only thing that justifies its price is its support. One of the best around.
The MacBook Pro comes with better hardware configurations that previous models but also with some downsides. Performance-wise it is a very fast laptop.
A 9th Gen Intel i7 six-core processor, 16 GB RAM, and an AMD Radeon Pro. There is also an option for an 8th Gen i9. The specs and operating system make it great for Scientific Computing.
Another great thing about the MacBook Pro is its battery life. It is able to last 9-10 hours of normal usage. On top of that, it weighs almost 4 pounds and a little over an inch thick.
It also has four Thunderbolt ports which you can connect to an external GPU or high-resolution monitors
Where the MacBook Pro goes wrong is its keyboard. It takes some getting used to because of its new design. In addition, there are no Type-A ports. All ports are Thunderbolt 3. You might have to get a dongle.
The Apple MacBook Pro is a powerful workstation. Along with its solid build quality and customer support from Apple makes it a futureproof laptop. One of the best laptops for processing large amounts of data.
The only downsides are its price tag, keyboard, and all Thunderbolt 3 ports.
3. DELL XPS 13/15
The Dell XPS 13 and XPS 15 are solid laptops for Scientific Computing. Both are Linux compatible. Both are powerful with the Dell XPS 15 being more powerful than the Dell XPS 13.
The Dell XPS 15 has an 8th Gen Intel i7 six-core processor whilst the Dell XPS 13 either comes with an 8th Gen quad-core i5 or quad-core i7 with lower clock speeds. But, the Dell XPS 13 is more lightweight and portable than the Dell XPS 15.
Having a laptop that is compatible with Linux is great especially in the field of bioinformatics. Linux provides a great environment for coding.
Because it is a stable and efficient operating system that can successfully host your environment for Scientific Computing and data analytics. On top of that, most data scientists recommend Linux.
Battery life from both is like marathon runners. Both are able to last close to half a day of normal usage.
The display differs between the two. The Dell XPS 13 has a 13.3 inch IPS and the XPS 15 is a 15 inch IPS. For the resolutions, the less expensive ones come with Full HD (1920 x 1080) and the latter with 4K (3840 x 2160) displays.
Both are lightweight, Dell XPS 13 weighs 2.65 pounds and the XPS 15 weighs one-and-half pounds heavier than it.
The downsides of Dell XPS 13 and 15 are their webcam placement which looks into your nose when in use. This can be adjusted by tilting the angle of the display.
And, the Dell XPS 9370 model doesn’t come with USB Type-A ports so you definitely need a dongle. Dell XPS 15 doesn’t have the USB port problem but rather port selection is well-balanced.
Dell XPS is a splendid laptop because of its performance, battery life, and portability. The Dell XPS 15 has a dedicated graphics card NVIDIA GTX 1050 Ti which is handy in deep learning projects. A solid option if you are pursuing Scientific Computing.
4. HUAWEI MATEBOOK X PRO
Solid aluminum unibody, beautiful display, and superb performance. The Huawei MateBook X Pro has one of the best price-to-performance ratios on the laptop market. On top of that, it has long battery life.
It sports a 13.9 inch 3K (3000 x 2000) thin bezel touchscreen display. Sharp, bright and color accurate make it a pleasant display to look at. The MateBook X Pro port selection is decent, a USB Type-C, Thunderbolt 3 and a USB 3.1 port.
The reason for its superb performance is a hardware configuration of an 8th Gen Intel i7 quad-core processor and 16 GB RAM. It also has a discrete graphics card MX150 which is entry-level.
The MX150 is only good enough for light gaming. AAA title games will not run smoothly unless you reduce the settings to low.
The storage is a 512 GB PCIe NVMe SSD. A fast storage device which also contributes to the performance of the laptop.
As mentioned earlier of its battery life it’s able to last 9-10 hours of normal usage. In addition, it’s one of the lightest laptops weighing almost 3 pounds and half an inch thick.
Because of its thinness, the Huawei MateBook X Pro tends to run hot. The webcam is also hidden.
A good idea if you care about your privacy. It shoots up from the keyboard when you activate it. The awkward position makes the webcam stare right into your nose. The fans also get loud when loads become heavy.
The Huawei MateBook X Pro is a good alternative to the MacBook Pro because of its similar build quality and battery life.
On top of that, it is lightweight and thin. Overall, a solid option with a good price-to-performance ratio.
5. ACER SWIFT 3
The Acer Swift 3 is an affordable ultrabook that can also be used for Scientific Computing. A solid aluminum body and a keyboard that delivers a comfortable typing experience. It is also light weighing 3.5 pounds.
Performance is not too shabby. It has an 8th Gen Intel quad-core i7 and 8 GB Ram. In addition to that, it has an entry-level MX150 graphics card for light gaming and a 256 GB SSD. Hardware configuration that will be able to provide you consistent solid performance.
The battery life is also decent averaging 8 hours of normal usage. The display could have been better.
A 14 inch Full HD (1920 x 1080) IPS. It is a glossy display so definitely there will be some reflections and viewing angles are also narrow.
All in all, the display is not much of a problem unless you work with a lot of colors. For the ports, it has two USB 3.0, a USB 3.1 and USB Type-C.
Overall, the Acer Swift 3 is a lightweight ultrabook that offers solid performance at an affordable price.
The only problem is it not so good display and bloatware. Bloatware can be easily taken care of and the display is not that bad.
6. ASUS VIVOBOOK S
The ASUS VivoBook S is a great laptop to start with if you are a beginner in Scientific Computing. An 8th Gen Intel i5 quad-core, 8 GB RAM and 256 GB SSD. Enough performance to do basic projects on.
On top of that, the keyboard is backlit and provides a comfortable typing experience. It has the right amount of tactile feedback and travel.
The port selection is decent, a USB Type-C, USB 3.0 and USB 2.0. Talking about thin and light, the ASUS VivoBook weighs almost 4 pounds and it is just a little over an inch thick.
Battery life is also above average lasting 8-9 hours of normal usage. Even though, ASUS claims the display is color rich in the specifications, it is really average.
The VivoBook sports a 15.6 inch Full HD (1920 x 1080) which has average color accuracy and reproduction. Sharpness and brightness are decent.
Nevertheless, the ASUS VivoBook is a great laptop to start learning Scientific Computing and analytics if you are a student or looking for something more affordable to buy.
You can always rely on cloud computing services if you think datasets need more computing power.