Corsair vs g.skill ram

Intel

2010.03.23 09:01 RandomMe Intel

/Intel is the community-run subreddit to talk about anything related to Intel Corporation and it's products. Intel's CPUs (i5, i7, i9, etc.), Graphics (ARC, Xe, UHD), Networking, OneAPI, XeSS, and all other Intel-related topics are discussed here.

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2020.11.27 12:06 hansnicolaim DingusAU's Subreddit

This subreddit is dedicated to the Twitch streamer DingusAU. https://www.twitch.tv/dingusau

[link]

2019.07.02 15:15 Gundam Breaker Mobile

Gundam Breaker Mobile from BANDAI NAMCO

[link]

2023.06.08 11:16 Outside_Till_7183 PC for VR

Hey guys :)
I would like to build a PC mostly for VR and I was wondering if following setup is fine: - Cpu: Intel Core i9-13900K, 3 GHz, 36 MB, BOX (BX8071513900K) - Fan: Endorfy Navis F360 (EY3B003) - Motherboard: MSI MPG Z790 CARBON WIFI - Ram: Corsair Vengeance RGB, DDR5, 32 GB, 7200MHz, CL34 (CMH32GX5M2X7200C34) - Psu: Corsair RM1000e ATX 3.0 1000W (CP-9020264-EU) - Gpu: Palit GeForce RTX 4090 GameRock OmniBlack 24GB GDDR6X (NED4090019SB-1020Q) - Ssd: Samsung 980 Pro 2 TB M.2-2280 PCIe 4.0 X4 NVME Solid State Drive
Is it ok? I'm not sure if 32 gb RAM is enough for VR?
What would you change in this setup?
What else would you add to this setup?

submitted by Outside_Till_7183 to buildapc [link] [comments]

2023.06.08 11:12 angry_pidgeon_123 i5 13600 and DDR optimal compatibility

Hello I'm building my own rig, so I need to ascertain optimal compatibility between parts for both performance and cost. My analysis I need help with, is what type of RAM in quantity and speed I need to install to optimize I5 13600 performance in gaming. Hope you understand my logic flow: CPU: Intel Core i5 13600K (https://www.intel.co.uk/content/www/uk/en/products/sku/230574/intel-core-i513600-processor-24m-cache-up-to-5-00-ghz/specifications.html) *supports dual channel, and runs up to 5Ghz in turbo, so buying 6Ghz (6000Mhz) RAM pointless? Obviously CPU supports 2 sticks, but not 4 sticks although some optimization can exist there I haven't heard of it... * furthermore, specs say I5 13600 supports up to DDR5 4800 MT/s. Dodging the hardware specifics details so I don't open a bigger can of worms, I jump to the point by example from google: "1600 MHz DRAM is thus capable of 3200 MT/s and is often sold simply as 3200 MHz" * * believing the CPU specs, it means DDR5 is supported, but up to which kind, unknown for sure * point of this discussion is, that I can buy RAM exactly or a little over spec, and save money

Then, I google up this: "What is 3200 mt s in RAM? MT/s vs MHz (Datarate vs Frequency) in RAM Modules. So, DDR4-3200 memory transmits data at a maximum rate of 3200 MT/s\*8 Bytes = 25,600 MB/s." \*\* \* since I5 13600 specs say it can achieve 76.8 GB/s, that means also from spec, DDR5 4800 MT/s \* 8 = 38.4 GB/s \* 2 (from dual channel!?) = 76.8 GB/s \* my conclusion based on potential insufficient data and coincidence, is that I should buy maximum DDR5-4800 with an I5 13600 processor", but DDR5-4800 does not mean having 4800Mhz (see \*) as it is sold, so what's the name of the DDR5 I want to buy exactly? I guess it would differ by manufacturer, since specs would differ, and even the naming might be misleading

I've been told this is good: Kingston FURY Renegade RGB 32GB (2x 16GB) 6000MHz DDR5 RAM (latency 32 kind, but in light of this discussion, it could be pointless if my system doesn't support it Another issue: if I only buy 32GB RAM, how is 76.8 GB/s relevant to me since the CPU can't read data that isn't there... meaning to actually use 76.8 GB/s I should have a minimum of 76.8 GB installed? Which means I should use software or games that actually occupy up to that much space simultaneously, and I admit I can only possibly fill up 32GB in gaming to the best of my ability, meaning I don't need by far 76.8GB/s, and could easily get away for years with say, 48GB total RAM in dual channel, just for slack... except, RAM caching should be a reality therefore having more RAM makes sense, but whether it is generally used would be the greatest unknown, and I would guess it's an issue since optimization isn't a concern for today's cheap software. Maybe some benchmarks would clear this issue up. My experience is, that in RAM there is only what the software loads up as it goes, and there is no precaching of resources generally except minimally so having more RAM won't enable software to become more efficient since it wasn't implemented to be so

I've also picked up another quote from google: "What's the Difference Between 2666MHz and 3200MHz? Most of the time, the difference is insignificant. The difference between 2666 MHz and 3200 MHz may be roughly 8 FPS. " \* which is relevant to me since I build my rig for gaming, and in FPS PVP 8 fps matters if the overall fps is 30, since you need a constant feel of the game to get into that zone where you constantly hit your targets, given prediction is necessary, which relies on stability. A difference of 8 FPS is significant since it means random spiking, not a constant a 8 FPS drop. If it can be constantly over 60 fps then it doesn't matter since the human eye can barely make out the difference. Therefore I want more Mhz for greater refinement of fps, but only to what the i5 13600 can handle, which comes back to the original question, does buying DDR5 6000 Mhz make any sense if the CPU's Mhz is 5000Mhz tops (or rather I won't OC beyond)?

P.S. With this, I plan to plant a RTX 4070, however the compatibility issues with CPU/RAM elude me completely, I need to look at the specs more, and take into account the motherboard of course since the video card is entirely reliant on that in the end. Maybe the CPU/RAM/MB is too slow for an RTX 4070, case in which I should buy a cheaper card. I will also ascertain in another post if necessary if top speed SSD makes sense with the other parts, and finally the motherboard I need to put it all together without paying for stuff I don't actually use or need

submitted by angry_pidgeon_123 to buildapc [link] [comments]

2023.06.08 10:38 mallikmallu Difference Between Data Scientist and Data Analyst

Difference Between Data Scientist and Data Analyst

Introduction

In the era of data-driven decision-making, the roles of data scientists and data analysts have gained prominence. These roles involve extracting insights from data, but data scientists and data analysts are the same regarding scope, skills, and responsibilities. This article aims to delve into the distinctions between data scientists and data analysts, shedding light on their job descriptions, primary tasks, and their value to organisations. By the end, you'll have a clearer understanding of how data scientists vs data analysts contribute to the broader field of data science and data analytics.

What Does a Data Analyst Do?

Data analysts play a pivotal role in organisations by transforming raw data into actionable insights. They are skilled at handling large datasets, cleaning and organising them for analysis. Data analysts work closely with stakeholders to understand their requirements and design analytical frameworks to address specific business questions. Data analysts contribute to the broader field of data science by utilising their expertise in statistical programming languages like Python or R to perform descriptive and diagnostic analytics.
Data analysts employ various statistical techniques and data visualisation tools to uncover patterns, trends, and correlations within the data. They leverage their expertise in statistical programming languages like Python or R to perform descriptive and diagnostic analytics. By conducting exploratory data analytics, they identify key metrics, generate reports, and present their findings to key stakeholders. These skills differentiate data analysts from data scientists, who possess a broader skillset and are involved in more complex tasks.
While data analysts focus on extracting insights from data, data scientists go a step further in data science. Data scientists possess advanced knowledge of machine learning algorithms, statistical modelling, and programming, allowing them to develop predictive models and solve complex problems. However, data scientists and analysts contribute to the broader field of data science and its applications in various industries. Data analytics can even help you fast-track your career in the supply chain field.
The insights provided by data analysts empower organisations to make informed decisions and take appropriate actions. By identifying trends, correlations, and outliers, data analysts enable businesses to uncover opportunities for improvement, identify potential risks, and optimise processes. Their work supports strategic planning, operational efficiency, and the overall growth of an organisation. Data analysts bridge the gap between raw data and valuable insights in the data science landscape, contributing to the larger field's data exploration and decision-making goals.
Data analysts play a crucial role in organisations by transforming raw data into actionable insights. They utilise statistical techniques, data visualisation tools, and programming languages to uncover patterns and trends within the data. Data analysts contribute to the broader field of data science by applying their skills in data cleaning, statistical analysis, and data visualisation. While they differ from data scientists in their skillset and responsibilities, data analysts provide valuable contributions to data science and its applications in various industries.
If you want to make a successful career in this field, an IT Certification course will help you land a good job. There are many options available in the market for you to choose from. Domain-specialised certification programs will help you get an edge over the others.

Data Analyst Job Description

Collecting and cleaning data: Data analysts gather relevant data from multiple sources, ensuring its accuracy and completeness. They clean and transform data to make it suitable for analysis.
Analysing and interpreting data: They apply statistical techniques to explore and summarise data, identifying trends and patterns. They use data visualisation tools to present their insights effectively.
They are generating reports: Data analysts create comprehensive reports highlighting key findings and actionable recommendations based on their analysis. These reports aid decision-making processes within the organisation.
Collaborating with stakeholders: They work closely with various teams, including business managers and data scientists, to understand their needs and provide data-driven insights to support strategic initiatives.
Monitoring data quality: Data analysts establish standards and ensure ongoing data accuracy and consistency.

What Does a Data Scientist Do?

Data scientists are professionals with strong mathematics, statistics, and computer science foundations. They possess advanced analytical skills and can solve complex problems by applying machine learning algorithms and statistical modelling techniques to large datasets. In data science, data scientists differentiate themselves from data analysts by delving deeper into the intricacies of data analytics and modelling.
Data scientists go beyond the traditional realm of data analytics and embrace the broader field of data science. They develop sophisticated models and algorithms to predict future outcomes and optimise decision-making processes. Their expertise in programming languages like Python or R and their knowledge of specialised tools like TensorFlow or PyTorch empower them to build and train predictive models that provide actionable insights.
While data analysts focus on extracting insights from data, data scientists employ advanced analytical techniques to uncover complex patterns and correlations. They leverage their mathematics, statistics, and programming skills to explore the available data's full potential. Data scientists play a vital role in data science by pushing the boundaries of what can be achieved with data and driving innovation in data analytics.
In data analytics, data scientists contribute to the broader field of data science by leveraging their advanced analytical skills and expertise. Their models and algorithms enable organisations to make informed predictions, optimise processes, and gain a competitive edge. By combining their knowledge of mathematics, statistics, programming, and domain expertise, data scientists provide valuable contributions to the field of data science and its applications in various industries.
Data scientists possess a strong foundation in mathematics, statistics, and computer science. They differentiate themselves from data analysts by applying advanced analytical techniques and developing sophisticated models and algorithms. In the realm of data science and data analytics, data scientists play a crucial role in extracting valuable insights from complex datasets and driving innovation in the field.
To become a successful data scientist, you should take data science courses from renowned institutions like Learnbay. It provides domain-specialised training that will give you an edge over other applicants.

Data Scientist Job Description

Data exploration and preprocessing: Data scientists acquire, clean, and transform data for analysis. They deal with unstructured data and apply advanced techniques for missing values and outliers.
Developing predictive models: They design and implement machine learning algorithms and statistical models to solve complex problems, leveraging their knowledge of algorithms, mathematics, and statistical methods.
Testing and evaluation: Data scientists rigorously test and evaluate the performance of their models, fine-tuning them to achieve optimal accuracy and efficiency.
Deploying models: They integrate models into production environments, ensuring scalability and reliability. It involves collaborating with software engineers and IT teams.
Continual learning and improvement: Data scientists stay updated with the latest advancements in data science and continually enhance their skills. They explore new algorithms and techniques to improve the accuracy and effectiveness of their models.

Data Scientists vs Data Analysts - Key Differences

Skillset: Data analysts possess specialised skills in data cleaning, statistical analysis, and visualisation, which are essential for conducting descriptive and diagnostic analytics. On the other hand, data scientists have a broader skillset encompassing advanced knowledge in mathematics, machine learning, and programming. It enables them to develop sophisticated predictive models and tackle complex problems.
Scope of analysis: Data analysts primarily work with structured data, exploring it through analysis to uncover insights and identify trends. In contrast, data scientists handle structured and unstructured data, leveraging machine learning algorithms and statistical models to make predictions and derive valuable insights.
Problem complexity: Data analysts typically focus on well-defined business questions and provide descriptive insights based on their analysis. In contrast, data scientists deal with more intricate problems that require them to develop and deploy models and algorithms. They often engage in exploratory research and experimentation to solve these complex challenges.
Decision-making impact: Data analysts support tactical and operational decision-making within organisations. Their insights provide valuable information for day-to-day operations. On the other hand, data scientists have a more significant impact on strategic decision-making. By delivering predictive models and actionable insights, they drive innovation and growth and shape the long-term direction of a business.
Technical expertise: Data analysts possess expertise in statistical analysis and data manipulation. They are proficient in tools and programming languages, enabling them to perform data cleaning, visualisation, and generate reports. In addition to statistical analysis and data manipulation, data scientists have advanced knowledge of machine learning algorithms, deep learning techniques, and statistical modelling and possess strong programming skills.
Job responsibilities: Data analysts are responsible for data cleaning, visualisation, and generating reports that provide descriptive and diagnostic insights to stakeholders. On the other hand, data scientists have a more comprehensive range of responsibilities. They engage in exploratory data analytics, develop and refine models, conduct testing and deployment, and collaborate with IT teams for scalable integration of their models into the organisation's systems.
Expected outcomes: Data analysts produce reports, dashboards, and visualisations that offer descriptive insights into the analysed data. Their work helps stakeholders understand past and current trends. On the other hand, data scientists generate predictive models, recommendations, and optimised solutions. Their work enables organisations to make informed decisions, predict future outcomes, and optimise processes to achieve desired outcomes.

Conclusion

In the realm of data science and data analytics, both data scientists vs data analysts play crucial roles. While data analysts uncover valuable insights from data and provide descriptive analysis, data scientists go further by developing predictive models and leveraging machine learning algorithms. Understanding the key differences between these roles helps organisations determine the expertise needed to extract maximum value from their data. By leveraging the strengths of both roles, businesses can make informed decisions, drive innovation, and gain a competitive edge in the data-driven landscape.

submitted by mallikmallu to datascience_AIML [link] [comments]

2023.06.08 10:37 -Vance- Making my first computer - Wouldn't say no to opinions/ tips/ help

As the title says, I'm making my first PC.
A year ago I got into game design, however while trying to swap my project over to unreal from unity, I have realised my current (very old) computer just won't cut it anymore! I have already bought two pieces of hardware, but have finally saved up enough to buy the rest, and would love some help/ input if possible. Please feel free to critique and offer opinions on my build choice as I know next to nothing about PC parts, brands etc other than what I have researched!

Thanks for any assistance/ critique given, I really appreciate it, and the time taken to comment! Cheers!

This is what I currently own:
AMD Ryzen 9 7950X CPU
https://www.pbtech.co.nz/product/CPUAMD07950X/AMD-Ryzen-9-7950X-CPU-16-Core--32-Thread---Max-Boo
ASUS ROG Strix NVIDIA GeForce RTX 3070 Ti OC 8GB GDDR6X Graphics Card
https://www.pbtech.co.nz/product/VGAAS33175/ASUS-ROG-Strix-NVIDIA-GeForce-RTX-3070-Ti-OC-8GB-G
These are the parts I am looking at getting to finish the PC (please let me know if you think there is a better alternatives or I have made a massive mistake)
Gigabyte X670 AORUS ELITE AX ATX For AMD Ryzen 7000 Series CPUs - AMD X670 Chipset - 4x M.2 - PCIe 5.0 (M.2) - 2x Internal USB 2.0 Header - 2x Internal USB 3.2 Header - 1x Internal Type C Header - 1x Internal TB Header - 1x 2.5 GbE - Wifi
https://www.pbtech.co.nz/product/MBDGBM36724/Gigabyte-X670-AORUS-ELITE-AX-ATX-For-AMD-Ryzen-700
Lian Li PC-O11D XL ROG Dynamic ROG Edition Full Tower Gaming Case RGB, Tempered Glass, White, CPU Cooler Supports Upto 167mm, Graphs Card Supports Upto 446mm, 360mm Rad Suported, 8X PCI Slots, Front: 4X USB 3.0, 1XType C, HD Audio, No PSU
https://www.pbtech.co.nz/product/CHALAN2046/Lian-Li-PC-O11D-XL-ROG-Dynamic-ROG-Edition-Full-To
NZXT Kraken X73 RGB 360mm AiO Water Cooling Kit 3x 120mm RGB Fans, Infinity Mirror, Rotatable Cap, Support Intel LGA 1700 / 1200 / 1151 / 1150 / 1155 / 1156 / 1366 / 2011-3, AMD AM5 / AM4 / TR4 (bracket provided by AMD CPU package)
https://www.pbtech.co.nz/product/WTRNZX0173/NZXT-Kraken-X73-RGB-360mm-AiO-Water-Cooling-Kit-3x
G.SKILL Flare X5 64GB DDR5 Desktop RAM Kit
https://www.pbtech.co.nz/product/MEMGSK192627/GSKILL-Flare-X5-64GB-DDR5-Desktop-RAM-Kit-2-x-32GB
Arctic Silver 5 High-Density Silver AS5-3.5G Thermal Compound 3.5-Gram Tube thermal grease paste Made With 99.9% Pure Silver
https://www.pbtech.co.nz/product/FANARC10535/Arctic-Silver-5-High-Density-Silver-AS5-35G-Therma
Crucial BX500 2TB 2.5" Internal SSD
https://www.pbtech.co.nz/product/HDDCRU22000/Crucial-BX500-2TB-25-Internal-SSD-SATA-6GBs---Up-t?qr=product_option
Microsoft Windows 11 Professional 64bit OEM Eng Intl 1PK DSP OEI DVD
https://www.pbtech.co.nz/product/OSYMSO3020/Microsoft-Windows-11-Professional-64bit-OEM-Eng-In
Manhattan Anti Static Wrist Strap 1.8M grounding cord Essential for static protection while working on PCs
https://www.pbtech.co.nz/product/WRIMAN0003/Manhattan-Anti-Static-Wrist-Strap-18M-grounding-co

Feel free to yell if I have missed any major component! Legend!

submitted by -Vance- to PcBuild [link] [comments]

2023.06.08 10:32 TheKnowledgeEgg Fans spinning, no output and no keyboard light up?

Just put the pc together and all fans are on. Plugged in hdmi in all slots and nothing. Plus the keyboard isn’t lighting up like it should either. Any ideas?
Parts are: Ryzen 5 7600 Gigabyte RTX 3060Ti OC Aorus B650M elite ax mobo Corsair ddr5 5600 ram 2x16gb Corsair HX850 psu
Cheers

submitted by TheKnowledgeEgg to buildapc [link] [comments]

2023.06.08 10:09 shypom I need help with random crash shutdown

Lately my computer got crash randomly and i must hard - shutdown ( no BDOS , only black screen , fan still spinning , VGA error on mainboard is show-up ) it to power it on again .
Most of time it only happen while i'm gaming and never happen in light work load .
I already change most of my hardware in last 3 month . Here is my spec
CPU : Ryzen 5 5600x ( was Ryzen 7 2700 )
Mainboard : X570s Gigabyte AERO G ( was x470 TUF Gaming )
PSU : Corsair RMx 1000 ( was Seasonic Focus 850W )
GPU : RX 6800 XT Gigabyte Gaming OC ( was Colorful igame RTX 3070 )
RAM : Corsair Vengance 32GB 3600 CL16 ( was 32 GBCorsair Tridenz 3000mhz )

Today i just found out in my services have a lot of services which suspect to me and i can't Disable it . I'm so tired of troubleshooting my PC . Please someone help me out

https://imgur.com/a/xH6mIs4

submitted by shypom to techsupport [link] [comments]

2023.06.08 09:40 michael2109 Corsair Vengeance - Unable to post with XMP and higher frequency

I've bought Corsair Vengeance 2x32GB DDR5 6600hz RAM. Looking in the bios it is set to 4500hz.
I would like to increase this to a higher amount so enable XMP and it automatically increases the frequency to 6600hz but it won't boot.
Is it possible for me to achieve the higher specs? If not I may aswell return them and buy lower spec RAM?

msi pro x670-p wifi
Ryzen 9 7950X
Corsair Vengeance 64GB (2x32) DDR5 6600hz

submitted by michael2109 to buildapc [link] [comments]

2023.06.08 09:29 Owlbearpigyy Yet another issue thread with the Arc 750

Hello everyone,
I've recently (March 2023) assembled a PC with the Intel Arc 750. It's been running fine until about in april, where the drivers were automatically updated by windows and the PC started getting BSODs whenever I was playing a game and for example running a youtube vid on the second monitor. So i stopped using my second monitor for a while and around may the drivers updated themselves again and that's where the shitshow began. At this point, doing almost anything caused my PC to just freeze up. My mouse would still be able to move, but whatever I clicked or whatever, nothing worked. The only thing that worked was to remove my HDMI cable and plug it back in. It seemed that whatever I clicked, did actually process, but it didn't update my on monitor. I basically couldn't do anything at this point because the monitor would 'freeze' whenever i opened a website or tried to start almost any application.
So after this happened (half may), i read up online about other people having issues and tried the following:
Enabling ReBAR Enabling Above 4G Decoding (As per Gigabyte instructions https://www.gigabyte.com/WebPage/785/NVIDIA_resizable_bar.html)
I would stil have the same issues where my monitor would freeze up and I couldn't do anything. So I used DDU to completely remove the drivers and install the ones from march, because those did work. And yes actualyl evreything was fine again! I could all the games I played, have my second monitor open and evreything. No BSODs, no lag whatsoever and I was happy! Until last week. For some reason, whenever I had my second monitor connected, the same issue appeared with my my mouse being able to move around, but whatever I did, wouldn't process on the screen. Removing the 2nd monitor would work acutally. But i'm in a pickle again, because it seems i'm constantly having issues with the GPU and at this point it's very annoying. It doesn't seem like my display drivers updated either, because I disabled that in Windows and didn't install Arc Control Center.
I want to try the following: Newer HDMI cables DP cables
Anyone else got any suggestions? Because at this point I just want to send back the videocard and buy whatever.
Full Specs:
CPU: 5800 X3D GPU: ASRock Intel Arc A750 Challenger D 8GB OC Motherbord: Gigabyte B550 Gaming X V2 (Updated firmware the moment we got it) RAM: G-Skill 2x 16GB PSU: Sharkoon 550 WPM Gold Zero Case: Corsair 4000D Airflow SSD: WD Blue SN570 1TB M2 Using HDMI Cables, no DP!

submitted by Owlbearpigyy to IntelArc [link] [comments]

2023.06.08 09:29 -Vance- Making my first computer - Wouldn't say no to opinions/ tips/ help

submitted by -Vance- to pcmasterrace [link] [comments]

2023.06.08 09:18 North_Band2191 Will this pc work

Im new to the pc community and i would like some advice on whether this pc would work/ be compatible
Cpu: Ryzen 5 3600 (second hand)
Gpu: Asus RTX 2060 gpu (second hand)
Cpu cooler: Artic freezer 34
Motherboard: Gigabyte B550M DS3H
Ram: 2x8gb of Corsair Vengeance RGB RS DDR4 DRAM
Storage: ADATA Ultimate SU650 M.2 2280 SSD 480 gb
Case: Tecware Forge M OMNI mATX
Power: COOLER MASTER MASTERWATT 550 semi-fanless modular 80+ Bronze
Thanks for any help

submitted by North_Band2191 to buildapc [link] [comments]

2023.06.08 08:42 Gysky New build...need Mb and case advice

Hi guys, I'm here because need some advice on my new build (replace my i56500+480...XD) mainly on MB and case (I want to keep this build for some years)...here the parts:
CPU...7800X3D (pc games, some VR and photo-editing 2d)
Cooler...noctua NH-d15S
RAM...32gb Corsair vengeance ddr5 6000mhz GPU...4070 ( pny,palit,inno3d I read they are all good brands and there is no many differences) MB... added a Asrock B650E Riptide , but don't know if it's a good MB or there is something better (Msi, Gigabyte) and here is my main concern, asrock its good? A B650 Pro RS will be enoght? Or it's better a Msi one like the Tomahawk? I'm really confused here. Case...I wanna keep my Cooler master MasterBox 5, or for nowdays it's better a new modern case with better airflow? (This is close in the upper side) Thanks so much for your time

submitted by Gysky to buildapc [link] [comments]

2023.06.08 08:39 Reklooz Torn between gpus

These are the cards available:
Rtx 3070 gigabyte gaming oc - €429 // Rx 6700xt Xfx qick - €439 // Rtx 3060 ti msi gaming trio - €389
My build:
Ryzen 5 3600x // Corsair ram 16gb 3200 // Tomahawk b450 max // Psu tx650m gold // Ssd nvme // Nzxt h510 case // Monitor Dell 2721dgf //
Will there be bottleneck problems playing at 1440p?

submitted by Reklooz to buildapc [link] [comments]

2023.06.08 08:35 befair1112342 Which ram to get for AM5 cpu?

My choices in my city are kinda limited. Probably getting 7600 or 7700(nonX) for casual gaming
Corsair 32GB (2x16GB) CMK32GX5M2E6000C36 Vengeance CL36 6000MHz DDR5 $159 [these are in Australian dollars]
Corsair 32GB (2x16GB) CMK32GX5M2B6400C32 Vengeance C32 6400MHz $196
Corsair Vengeance RGB 32GB (2x16GB) 6400MHz CL32 DDR5 CMH32GX5M2B6400C32 $229
G.Skill Flare X5 32GB (2X16GB) DDR5-6000 CL32 Memory [F5-6000J3238F16GX2-FX5]. $210
G.Skill Trident Z5 Neo 32GB (2x16GB) 5600MHz CL30 DDR5 EXPO $229
Corsair Vengeance RGB 32GB (2x16GB) 6000MHz CL30 DDR5 EXPO Grey $249

submitted by befair1112342 to pcmasterrace [link] [comments]

2023.06.08 08:32 Eternally_Yawning A potential issue with Ryzen 5800x or something else?

I'm currently running:

Processor: AMD Ryzen 7 5800X 8-Core Processor - 3.80 GHz
GPU: EVGA 3070
RAM: Corsair vengeance LPX DDR4, 32.0 GB
MB: Asus ROG Strix b550-E gaming
PSU: Corsair 750w Gold rated, fully modular
Storage: x2 Samsung Evo 1Tb
64-bit operating system, x64-based processor
Windows 10 Home, Version - 22H2, OS build - 19045.2965

Symptoms/ issues that have occurred include:

Screen freezing/ unresponsive (actually happened while writing this, interestingly enough)
The screen lags and turns on/off intermittently, or at least goes black as if it is off. I have noticed when I bring up Task manager on at least one occasion that the CPU usage was at 100% in that case for Google.
Freezing for a brief period, then the PC restarts itself unprompted.

*I'm not entirely sure if these are all related to the same problem, tbh, but they are the main issues I have experienced
Please let me know if you need more information, and I will see what I can provide.
Since January, I have been plagued with this issue that randomly shows up. If anyone has encountered this problem before and knows a possible solution, it would be greatly appreciated!

submitted by Eternally_Yawning to buildapc [link] [comments]

2023.06.08 08:19 GoldFu1on95 Which DDR5 ram to get?

G.Skill Flare X5 32 GB (2 x 16 GB) DDR5-6000 CL36 Memory	$149.97
G.Skill Flare X5 32 GB (2 x 16 GB) DDR5-6000 CL32 Memory	$159.97
G.Skill Ripjaws S5 32 GB (2 x 16 GB) DDR5-6000 CL30 Memory	$149.97
G.Skill Ripjaws S5 32 GB (2 x 16 GB) DDR5-6400 CL32 Memory	$154.99

I am planning on pairing the RAM with 7800x3d, Asus b650e-i mobo and 4090fe. If that helps narrow things down.

submitted by GoldFu1on95 to buildapc [link] [comments]

2023.06.08 08:19 jasndream Motherboard recommendation for my first PC build

Planning to build a pc and still contemplating about the mobo which is asus 320m, build is Ryzen 3600 Gtx 1660 super (used) 16 gb ram (2 x 8gb) 750 W corsair psu 2 tb hdd 500 gb ssd What are the pros and cons of using the Asus 320M K mobo?

submitted by jasndream to PHbuildapc [link] [comments]

2023.06.08 08:17 ClubbPenguinn Help me with my pc build please

Greetings everyone,I'm in australia and in the process of assembling a PC, and I would appreciate your insights to ensure that I'm making the most suitable choices for my needs. Primarily, I'll be using this PC for Unreal game development and VR gaming. Therefore, I'm aiming to future-proof it as much as possible, even if it means spending a bit more.My budget for this build is $5,500. Currently, the components I've selected below total around $5,000. I'm open to suggestions regarding potential changes or upgrades, whether it's swapping out for a different brand, considering different RAM speeds, or any other modifications you might recommend.On the other hand, if you believe that my current build is already more than sufficient or even overkill for my intended use, I would appreciate that feedback as well. I'm eager to hear your thoughts, and I thank you in advance for your time and expertise.
PC specs13th gen Intel Core i7 13700K CPUGigabyte B760M Gaming X AX DDR5 MotherboardCorsair iCUE H150i Elite 360mm LCD Display Liquid CPU CoolerFractal Design Torrent Tempered Glass Dark Tint Case BlackCorsair RM1000x Gold Modular 1000W Power Supply V2EK CryoFuel Clear Premix 1000mLThermal Grizzly Kryonaut Thermal Grease 3mlGigabyte Dual Band WiFi 6 AX PCIe Wireless AdapterPCCG Black Cable Ties 100 pack - 2.5mm x 200mmSamsung 980 PRO M.2 PCI-E Gen4 NVMe SSD 2TB with HeatsinkGigabyte GeForce RTX 4080 Aorus Master 16GBCorsair Vengeance 64GB (2x32GB) 5200MHz CL40 DDR5
Total $4920

submitted by ClubbPenguinn to PcBuild [link] [comments]

2023.06.08 08:16 ClubbPenguinn Help me With my current pc build please

Greetings everyone,I live in australia and in the process of assembling a PC, and I would appreciate your insights to ensure that I'm making the most suitable choices for my needs. Primarily, I'll be using this PC for Unreal game development and VR gaming. Therefore, I'm aiming to future-proof it as much as possible, even if it means spending a bit more.My budget for this build is $5,500. Currently, the components I've selected below total around $5,000. I'm open to suggestions regarding potential changes or upgrades, whether it's swapping out for a different brand, considering different RAM speeds, or any other modifications you might recommend.On the other hand, if you believe that my current build is already more than sufficient or even overkill for my intended use, I would appreciate that feedback as well. I'm eager to hear your thoughts, and I thank you in advance for your time and expertise.
PC specs13th gen Intel Core i7 13700K CPUGigabyte B760M Gaming X AX DDR5 MotherboardCorsair iCUE H150i Elite 360mm LCD Display Liquid CPU CoolerFractal Design Torrent Tempered Glass Dark Tint Case BlackCorsair RM1000x Gold Modular 1000W Power Supply V2EK CryoFuel Clear Premix 1000mLThermal Grizzly Kryonaut Thermal Grease 3mlGigabyte Dual Band WiFi 6 AX PCIe Wireless AdapterPCCG Black Cable Ties 100 pack - 2.5mm x 200mmSamsung 980 PRO M.2 PCI-E Gen4 NVMe SSD 2TB with HeatsinkGigabyte GeForce RTX 4080 Aorus Master 16GBCorsair Vengeance 64GB (2x32GB) 5200MHz CL40 DDR5
Total $4920

submitted by ClubbPenguinn to PcBuildHelp [link] [comments]

2023.06.08 08:15 befair1112342 Which ram to get? For AMD 7700

Corsair 32GB (2x16GB) CMK32GX5M2E6000C36 Vengeance CL36 6000MHz DDR5 $159
Corsair Vengeance RGB 32GB (2x16GB) 6400MHz CL32 DDR5 CMH32GX5M2B6400C32 $229
Corsair 32GB (2x16GB) CMK32GX5M2B6400C32 Vengeance C32 6400MHz $196
G.Skill Flare X5 32GB (2X16GB) DDR5-6000 CL32 Memory [F5-6000J3238F16GX2-FX5]. $210
G.Skill Trident Z5 Neo 32GB (2x16GB) 5600MHz CL30 DDR5 EXPO $229
Corsair Vengeance RGB 32GB (2x16GB) 6000MHz CL30 DDR5 EXPO Grey $249

submitted by befair1112342 to bapcsalesaustralia [link] [comments]

2023.06.08 08:07 webdev20 Redis vs MongoDB: Which Database Suits Your Needs?

Application development world, one decision that holds profound implications for your project's success is the selection of an appropriate database. This choice is far from trivial. It directly impacts not only the performance of your application, delivering a smooth or laggy user experience, but also its scalability, determining whether your application can grow in stride with your user base or customer demand. Additionally, your database choice also influences the ease or complexity of managing your application, affecting how swiftly you can respond to issues and implement changes or improvements.
In the diverse landscape of database solutions, two names often rise to the forefront of discussions - Redis and MongoDB. These popular options each bring a distinctive set of features and advantages to the table, suiting them to different scenarios and requirements. As a result, they are frequently contrasted and compared, with developers seeking to discern which would be the ideal fit for their specific project needs.
Redis, standing for Remote Dictionary Server, is an open-source, in-memory data structure store. It can function as a database, cache, and message broker. The design of this key-value store results in lightning-fast read and write operations. This quality makes Redis a prime candidate for applications that necessitate real-time data processing.
On the other hand, MongoDB is a document-oriented database known for its flexibility and scalability. It is also open-source and employs JSON-like documents with optional schemas. These attributes make MongoDB a powerful tool for querying and indexing, further enriching its appeal.
Both Redis and MongoDB, with their unique strengths and characteristics, have carved niches for themselves in certain types of applications. However, the choice between them is not always clear-cut and can be influenced by a multitude of factors such as the nature of data to be stored, speed requirements, scalability needs, and more.
The goal of this comprehensive article is to illuminate the key facets of Redis vs MongoDB. By contrasting their features, strengths, and weaknesses, we aim to equip you with the necessary understanding to navigate this critical decision confidently. Through this guidance, we hope to steer you towards the right choice for your project, optimizing the performance, scalability, and manageability of your application.

What is Redis?

Redis, an acronym for Remote Dictionary Server, is an open-source, in-memory data structure store used as a database, cache, and message broker.
At the heart of our comparison lies Redis. An acronym that stands for Remote Dictionary Server, Redis is a potent and versatile solution in the data management space. It is an open-source tool, meaning that its source code is freely available, promoting transparency, community-driven enhancements, and adaptability to specific needs. The free availability of its source code aligns with the ethos of many developers, supporting the continued development and refinement of this high-performing software.
Redis operates as an in-memory data structure store, which significantly impacts its performance characteristics. The term 'in-memory' signifies that Redis stores data directly in the server's main memory (RAM), unlike other databases that store data on disk. This characteristic provides Redis with a substantial speed advantage, as accessing data in memory is considerably faster than retrieving it from a disk. As a result, applications using Redis can access and manipulate data with blazing speed, propelling their performance.
The versatility of Redis goes beyond just functioning as a database. It can also serve as a cache and message broker. As a cache, Redis temporarily stores frequently accessed data to reduce the time taken for data retrieval, resulting in faster response times. As a message broker, Redis supports the publishing of messages and subscribing to channels, facilitating efficient and real-time communication between different parts of an application.
Redis adopts a straightforward and effective key-value store design, allowing data to be stored as a pair where one element is a key, and the other is its corresponding value. This architecture is simple yet powerful, enabling high-speed read and write operations. Keys provide a method to identify data, and values hold the actual data itself. Due to this design, Redis excels in applications requiring real-time data processing where speed is of the essence.
Overall, the nature of Redis - its open-source status, its in-memory operation, its versatile roles, and its key-value store design - makes it an outstanding choice for certain types of applications. Especially in scenarios where real-time data processing is vital, Redis can offer a performance that truly sets it apart.

The Benefits of Redis: Speed, Flexibility, and More

Redis, as we've discovered, is much more than a simple data store. Its unique characteristics endow it with certain strengths that make it a robust tool in a developer's arsenal. The benefits of Redis are many, but two in particular stand out: its remarkable speed and its support for a range of diverse data structures.
Redis owes its blazing speed to its in-memory design. As data is stored and accessed directly from the main memory (RAM), data operations like read and write occur at a rapid pace. With Redis, you can achieve sub-millisecond latency, a speed that is often essential in today's dynamic and fast-paced applications. This speed advantage places Redis in a class of its own when it comes to applications that require real-time responses.
In practical terms, this means that Redis is an ideal solution for numerous demanding use-cases. For instance, as a cache, Redis can store frequently accessed data for speedy retrieval, effectively reducing application response times. It also shines in session management, where maintaining a fast, consistent experience for users across multiple sessions is crucial.
The application of Redis doesn't stop there. In real-time analytics, where data needs to be processed and insights need to be drawn instantly, Redis proves to be a valuable asset. Additionally, it is an excellent fit for message queuing systems, where its ability to quickly publish and retrieve messages ensures efficient and reliable communication between different application components.
Complementing its speed is another significant strength of Redis: its support for a wide array of data structures. Redis is not just a simple key-value store; it can handle data structures such as lists, sets, sorted sets, hashes, bitmaps, hyperloglogs, and geospatial indexes. Each of these data structures serves a unique purpose, and having the ability to choose the right one for the right task can be instrumental in building efficient applications.
This diversity in data structures offers a high degree of flexibility in handling different data types and use cases. For example, lists in Redis can be used to implement stacks, queues, or even a timeline of activities; sorted sets can be used to manage a leaderboard in a gaming application; and geospatial indexes can be used in location-based services like finding the nearest restaurant.
The pros of Redis lie in its exceptional speed and its support for various data structures. These advantages make Redis a compelling choice for a range of applications, from those requiring real-time data processing to those requiring diverse methods of data handling.

Cons of Redis

While Redis is indeed a powerful tool with a multitude of strengths, it is not without its limitations. Understanding these constraints is critical to making an informed decision about whether Redis is the right choice for your application's needs. The two primary limitations of Redis relate to its data persistence model and its relatively simple querying capabilities.
The first limitation revolves around Redis' data persistence model. As previously discussed, Redis is fundamentally an in-memory data store, meaning data is primarily stored in the server's main memory (RAM). While this design leads to fast data access and superior performance, it also means that data stored in Redis may not persist if the server is rebooted or encounters a failure.

Although Redis does offer mechanisms to mitigate this concern, such as snapshotting and append-only files (AOF) that allow data to be persisted to disk, these methods come with their own trade-offs in terms of performance and disk space. As a result, Redis may not be the best choice for scenarios where long-term, reliable data storage is paramount. Applications requiring a strong guarantee of data durability may need to consider alternative solutions or additional backup strategies.
The second limitation of Redis pertains to its querying capabilities. At its core, Redis operates as a key-value store, where data can be quickly accessed using a unique key. While this design works well for simple data access patterns and contributes to Redis' impressive speed, it may fall short in scenarios requiring more complex data manipulation.

Unlike databases that support SQL or similar querying languages, Redis lacks advanced querying capabilities. You cannot, for instance, easily perform operations like selecting all keys that meet a certain condition or joining data from multiple keys. As a result, Redis may be less suited to scenarios that demand intricate data analysis, complex searches, or advanced data manipulation.
In essence, while Redis is a high-performance in-memory data store that supports a range of data structures, it is not a one-size-fits-all solution. The limitations concerning data persistence and querying capabilities should be carefully considered alongside its strengths. The right decision always depends on your specific use case, requirements, and constraints. As with any technology decision, the goal is to choose the best tool for the task at hand.

What is MongoDB ?

MongoDB is an open-source, document-oriented database, meaning it stores data in a semi-structured format similar to JSON (JavaScript Object Notation), known as BSON (Binary JSON).
Like Redis, being open-source, MongoDB's source code is freely accessible, fostering a culture of innovation, transparency, and community-backed improvements.
One of MongoDB's most significant selling points is its use of JSON-like documents with optional schemas. This design choice marks a stark departure from traditional relational databases that employ structured tables and rows for data storage. In MongoDB, data is stored and organized in documents, which can contain multiple fields and data types, offering a great deal more flexibility. These fields can vary from document to document, and there's no obligation to have a predefined schema. This lack of rigidity allows developers to adapt the database structure as the application requirements evolve, making MongoDB an excellent choice for projects where the data schema might change over time.

Another standout characteristic of MongoDB is its high scalability. As businesses grow and applications generate more data, the ability of a database to scale becomes paramount. MongoDB shines in this regard, providing features like automatic sharding and replication to handle vast amounts of data and distribute it across multiple servers. Sharding allows MongoDB to distribute data across several machines, efficiently managing large data sets. Replication, on the other hand, ensures data availability and durability by maintaining multiple copies of data across different database servers.
Beyond flexibility and scalability, MongoDB also boasts powerful querying and indexing capabilities. Unlike Redis, which primarily operates as a key-value store, MongoDB provides a rich query language that allows developers to perform complex read and write operations. Whether it's filtering data based on specific criteria, joining data across collections, or performing aggregate functions, MongoDB's querying language has got you covered.

Furthermore, MongoDB supports a variety of indexes, making data retrieval even faster. Developers can create indexes on any field within a MongoDB document, including fields within arrays, improving performance and efficiency.
MongoDB, with its open-source nature, document-oriented structure, flexible schema, high scalability, and robust querying and indexing capabilities, stands out as a potent solution for a wide array of applications. It is particularly fitting for scenarios where data schemas are flexible, large volumes of data are expected, or where complex querying and indexing are required.

The Benefits of MongoDB: Flexibility, Scalability, and Reliability

MongoDB, a favored choice among many developers and businesses alike, is characterized by a multitude of strengths. These strengths revolve around MongoDB's flexibility, rich querying capabilities, scalability, and ACID-compliant transactions, all of which contribute to its suitability for handling complex data structures, big data applications, and business-critical operations.
First and foremost, the flexibility that MongoDB offers is significant. MongoDB does not impose a rigid schema on your data, a departure from traditional SQL databases. This schema-less nature means you can store documents of varying structures within the same collection, allowing you to handle data that is inconsistent or evolving. You can add, remove, or modify fields as you go, which is particularly useful in applications where the data structure might change over time.
This flexibility extends to MongoDB's powerful querying capabilities. MongoDB provides a rich query language that supports a wide range of operations, allowing developers to perform complex tasks that go far beyond simple data retrieval. Whether you're filtering documents based on specific criteria, joining data across multiple collections, or performing aggregation functions, MongoDB offers the capabilities you need. This makes it especially suitable for handling complex data structures and requirements.
Next, MongoDB's strength lies in its scalability. It is designed to accommodate big data applications and scale horizontally through a process called sharding. Sharding is the practice of distributing data across multiple servers or clusters, which can enhance performance, manage large data sets efficiently, and ensure that your application can grow without being constrained by your database's capacity.
If you're handling big data or expecting high growth rates, MongoDB's sharding capabilities can help maintain high performance and prevent the database from becoming a bottleneck. This makes MongoDB a preferred choice for big data applications where scalability is a key requirement.
Finally, MongoDB is ACID-compliant, supporting Atomicity, Consistency, Isolation, and Durability (ACID) transactions. This compliance ensures that all database transactions are processed reliably and that your data remains consistent even in the event of a system failure. ACID compliance is a crucial factor for many business-critical applications where data integrity and reliability cannot be compromised.
In essence, MongoDB's flexibility, rich querying capabilities, scalability, and ACID-compliant transactions make it a robust, versatile, and reliable choice for a variety of applications. Whether you're handling complex and varying data structures, managing big data, or dealing with business-critical operations that require reliable data processing, MongoDB has the strengths to meet these challenges.

Cons of MongoDB: Memory Consumption and Data Redundancy

Like all technologies, MongoDB is not without its drawbacks. It's essential to understand these limitations to make an informed decision about whether it's the right database solution for a particular use case. Two notable limitations associated with MongoDB are its sizable memory footprint and potential for data redundancy and inconsistency due to its document-oriented design.
Firstly, MongoDB has a reputation for being relatively memory-intensive. As a document-oriented database that maintains a variety of indexes to facilitate quick data retrieval, MongoDB requires a substantial amount of memory. This is particularly true when dealing with large datasets, as MongoDB keeps frequently accessed data and indexes in RAM to boost performance. In resource-constrained environments, this can pose a challenge. If your application is running on a device or server with limited RAM, MongoDB's large memory footprint could lead to suboptimal performance or even outages.
Moreover, while MongoDB is highly performant and can handle big data with ease, it may not perform as well as some alternatives, like Redis, for in-memory data handling. Redis is specifically designed for in-memory operations, offering exceptional speed and performance. So, if your application requires real-time data processing and instant data access, Redis may outperform MongoDB.

Secondly, while MongoDB's flexible, document-oriented approach is one of its biggest strengths, it can also lead to challenges. The lack of a predefined schema means that the same data can be represented in multiple ways across different documents. This flexibility, while advantageous in many scenarios, can lead to data redundancy if not managed correctly.
For instance, if the same piece of data is stored in multiple documents, any changes to that data must be updated across all instances, increasing the complexity of data management. If these updates aren't performed correctly, it can lead to data inconsistency issues. These challenges can be mitigated with careful database design and data management practices, but they nonetheless represent a trade-off of MongoDB's flexible, schema-less design.
While MongoDB is a powerful, flexible, and scalable database solution, these strengths come with trade-offs. The database's memory footprint and potential for data redundancy and inconsistency are important factors to consider when deciding if MongoDB is the right choice for your project. As always, the optimal database choice depends on your specific use-case, the resources at your disposal, and the constraints you're working under.

Redis vs MongoDB: Making the Right Choice

Embarking on the journey to select the right database for your application can feel like navigating a complex maze. Two potent contenders that often cross paths are Redis and MongoDB. Both have distinct strengths, and the ultimate decision largely hinges on your unique use case and specific requirements.
Redis can be your ally when your application demands lightning-fast data operations. Its in-memory nature and simplified data model provide unparalleled speed, offering sub-millisecond latency. If your application requires a robust caching system or real-time analytics, Redis shines bright as a choice. For instance, if you're building a chat application, a gaming leaderboard, or an ad-serving system where speed is critical, Redis can help you deliver an excellent user experience.
Furthermore, Redis is also an excellent fit for storing session information and user profiles. Many applications need quick access to user data for authentication and personalization, and the blazing-fast read and write operations that Redis provides can make these tasks significantly more efficient. The data structures that Redis supports, such as lists, sets, and hashes, can accommodate these scenarios well, further underlining why Redis could be the right choice for such requirements.
MongoDB comes into the picture when your application requires the handling of complex querying, high scalability, and flexibility in dealing with diverse and evolving data structures. MongoDB's document-oriented design and rich query language make it a powerful tool for applications that need to process complex data and perform sophisticated queries. It's ideally suited for projects like content management systems, mobile applications, and real-time analytics that require flexibility and robustness.
MongoDB's ability to scale horizontally through sharding makes it a reliable ally for applications expecting high data growth. As your application expands and the data multiplies, MongoDB's sharding capabilities ensure that your database doesn't become a performance bottleneck.

While comparing Redis vs MongoDB, it's crucial to remember that choosing a database isn't always a binary decision. The realm of application development is replete with examples of successful applications that employ a polyglot persistence architecture, effectively leveraging the strengths of multiple databases. For instance, you could choose MongoDB for storing business data that requires complex querying and flexibility, while simultaneously employing Redis for caching and session storage to capitalize on its speed. This approach allows you to bring together the best of both worlds, thereby enhancing the performance and efficiency of your application.
The journey to choose between Redis vs MongoDB should be guided by a thorough understanding of your application's requirements and the unique strengths of each database. By aligning these elements, you can make a well-informed decision that propels your application towards success.

Conclusion

Arriving at the juncture of decision-making, the path you tread in choosing the right database is laden with significance. This decision can profoundly impact multiple facets of your application, including its performance, scalability, efficiency, and long-term viability. The choice between Redis and MongoDB is no exception and warrants a thorough understanding of your application's needs, paired with the unique strengths each database brings to the table.
When it comes to database selection, the key is to immerse yourself in understanding your application's unique needs and demands. Does your application need to handle real-time analytics, where speed is paramount? Or perhaps you're developing a content management system that requires complex querying and a flexible data structure? Each use case presents unique needs that can be met more effectively by one database over the other.
Understanding the strengths of Redis and MongoDB is equally important in this equation. Redis, with its in-memory design and blazing-fast read and write operations, shines in situations demanding high-speed data operations, caching, and real-time analytics. Simultaneously, MongoDB, with its flexibility, rich querying language, and high scalability, proves to be a robust choice for applications dealing with diverse, evolving data structures, and expecting high data growth.
Once you've identified your application's needs and understood how each database can address these requirements, you're well-equipped to make an informed choice. This process may be intricate, but it's crucial to remember that it's not a race, but a journey. The goal is not to rush to a decision, but to carefully consider all the factors involved.
Remember, technology choices, like selecting a database, are not static, and you may need to reassess your decision as your application evolves and grows. By staying adaptable, continuously learning, and keeping the focus on your application's needs, the task of choosing the right database becomes less daunting and more of an enriching journey.
In conclusion, whether you choose Redis, MongoDB, or a combination of both, the objective is to align the database's strengths with your application's needs. This informed and balanced approach will ensure your application's robust performance and scalability, positioning it for long-term success. This may seem like a complex puzzle, but with a clear understanding of your application's needs and the strengths of each database, you're well on your way to solving it.

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2023.06.08 07:46 badboysherlock Pc freezing and crashing while playing fifa 23

Hello, looking for help diagnosing an issue I've run into, my pc freezes and crashes 5 mins into fifa 23. The menus all run fine, but when i load into a division rivals match and play, it freezes, and then the pc restarts. (ingame settings all low, running at native 1080p)
Ive logged monitoring stats in HWinfo, and I can share the file, if someone could help me understand if anything's wrong.
PC specs -
Cpu - intel i5-12600kf with cooler master hyper 212 argb turbo fan- all core overclock to 4.8ghz, disabled c states and all e cores
Gpu - amd rx6600xt (msi mech 2x) - no oc, stock fans, on nimerzone drivers 23.4.1 (22.5.1 kernel)
Ram - 16gb ddr4 corsair vengeance 3200 (single stick)
Drives - Samsung 980 NVMe M.2 500 GB SSD (game root dir), 1tb WD Seagate hard drive
MOBO - MSI Pro Z690 A DDR4
PSU - Antec CSK 650W 80 Plus Bronze Series 650 Watt Power Supply
Case -Ant Esports ICE-280TG White Mid Tower Gaming Cabinet
This is the HWinfo log file. Where it ends is where the pc crashed.
[https://u.pcloud.link/publink/show?code=XZ5yiEVZh8PkYhzMwnSKWPhBKS36NyOSbqaV]
Ive tried reinstalling drivers, it hasn't helped. Im on the latest preview update of windows (KB5026443). Other drivers are up to date. I have the game installed on Steam. Also this only started happening after the latest update, i had no issues like 3 months ago. I stopped playing then because my controller had issues. I play apex legends (lowest settings, cap to 144) and the game runs fine. Ive also tried verifying integrity of files on steam for fifa 23.
UserBenchmarks: Game 110%, Desk 109%, Work 108% CPU: Intel Core i5-12600KF - 100.6% GPU: AMD Radeon RX 6650 XT - 109.8% SSD: Samsung 980 NVMe PCIe M.2 500GB - 258.2% HDD: WD Blue 1TB (2012) - 88% RAM: Corsair Vengeance LPX DDR4 3200 C16 1x16GB - 59.3% MBD: MSI PRO Z690-A DDR4
[url=https://www.userbenchmark.com/UserRun/61978824]

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2023.06.08 07:44 TripleStufOreos College laptop for Comp Sci US 1400-1600

LAPTOP QUESTIONNAIRE

Total budget (in local currency) and country of purchase. Please do not use USD unless purchasing in the US: 1600$ at most, can use student discount at like apple, etc.
Are you open to refurbs/used? no
How would you prioritize form factor (ultrabook, 2-in-1, etc.), build quality, performance, and battery life?
1. Build Quality, 2. Performance, 3. Battery Life, don't need 2-1 or ultrathin
How important is weight and thinness to you? Nothing absolutely massive, the thinner the better.
Do you have a preferred screen size? If indifferent, put N/A. 14-15" would be great but open to 13
Are you doing any CAD/video editing/photo editing/gaming? List which programs/games you desire to run. Needs to run some games, but general cs apps for the most part.
If you're gaming, do you have certain games you want to play? At what settings and FPS do you want? If PC, at least 1080p 100 fps on FIFA 23, R6 Siege, if mac not worried
Any specific requirements such as good keyboard, reliable build quality, touch-screen, finger-print reader, optical drive or good input devices (keyboard/touchpad)? will need a nice display ideally, at least 144hz,, needs at least 16gb ram, 512gb SSD, and have at least 2 usb-c ports.
Leave any finishing thoughts here that you may feel are necessary and beneficial to the discussion. Mostly wondering if anyone has experience in the last few years of using a MB pro vs a windows machine for computer science, and if you think I should go windows, what laptop would be good for what I need

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