According to a TrendForce survey report, the AI ??wave has a significant impact on the DRAM memory and NAND flash memory markets. In this site’s news on May 7, TrendForce said in its latest research report today that the agency has increased the contract price increases for two types of storage products this quarter. Specifically, TrendForce originally estimated that the DRAM memory contract price in the second quarter of 2024 will increase by 3~8%, and now estimates it at 13~18%; in terms of NAND flash memory, the original estimate will increase by 13~18%, and the new estimate is 15%. ~20%, only eMMC/UFS has a lower increase of 10%. ▲Image source TrendForce TrendForce stated that the agency originally expected to continue to

Local fine-tuning of DeepSeek class models faces the challenge of insufficient computing resources and expertise. To address these challenges, the following strategies can be adopted: Model quantization: convert model parameters into low-precision integers, reducing memory footprint. Use smaller models: Select a pretrained model with smaller parameters for easier local fine-tuning. Data selection and preprocessing: Select high-quality data and perform appropriate preprocessing to avoid poor data quality affecting model effectiveness. Batch training: For large data sets, load data in batches for training to avoid memory overflow. Acceleration with GPU: Use independent graphics cards to accelerate the training process and shorten the training time.

1. First, enter the Edge browser and click the three dots in the upper right corner. 2. Then, select [Extensions] in the taskbar. 3. Next, close or uninstall the plug-ins you do not need.

LaravelEloquent Model Retrieval: Easily obtaining database data EloquentORM provides a concise and easy-to-understand way to operate the database. This article will introduce various Eloquent model search techniques in detail to help you obtain data from the database efficiently. 1. Get all records. Use the all() method to get all records in the database table: useApp\Models\Post;$posts=Post::all(); This will return a collection. You can access data using foreach loop or other collection methods: foreach($postsas$post){echo$post->

Algorithms are the set of instructions to solve problems, and their execution speed and memory usage vary. In programming, many algorithms are based on data search and sorting. This article will introduce several data retrieval and sorting algorithms. Linear search assumes that there is an array [20,500,10,5,100,1,50] and needs to find the number 50. The linear search algorithm checks each element in the array one by one until the target value is found or the complete array is traversed. The algorithm flowchart is as follows: The pseudo-code for linear search is as follows: Check each element: If the target value is found: Return true Return false C language implementation: #include#includeintmain(void){i

JVM command line parameters allow you to adjust JVM behavior at a fine-grained level. The common parameters include: Set the Java heap size (-Xms, -Xmx) Set the new generation size (-Xmn) Enable the parallel garbage collector (-XX:+UseParallelGC) Reduce the memory usage of the Survivor area (-XX:-ReduceSurvivorSetInMemory) Eliminate redundancy Eliminate garbage collection (-XX:-EliminateRedundantGCs) Print garbage collection information (-XX:+PrintGC) Use the G1 garbage collector (-XX:-UseG1GC) Set the maximum garbage collection pause time (-XX:MaxGCPau

Redis persistence will take up extra memory, RDB temporarily increases memory usage when generating snapshots, and AOF continues to take up memory when appending logs. Influencing factors include data volume, persistence policy and Redis configuration. To mitigate the impact, you can reasonably configure RDB snapshot policies, optimize AOF configuration, upgrade hardware and monitor memory usage. Furthermore, it is crucial to find a balance between performance and data security.

Redis memory size setting needs to consider the following factors: data volume and growth trend: Estimate the size and growth rate of stored data. Data type: Different types (such as lists, hashes) occupy different memory. Caching policy: Full cache, partial cache, and phasing policies affect memory usage. Business Peak: Leave enough memory to deal with traffic peaks.