Tag: Optimizations

Memory Optimizations in Android

Memory optimization is an important aspect of developing any software, and it is particularly crucial in mobile applications where resources are often limited. Android, being the most popular mobile operating system, has a wide variety of devices with varying memory capacities and configurations. To...

Auditor’s Advice: Math, Solidity & Gas Optimizations | Part 1/3

We continue our series of educational articles and today we’ll look at some specific tips for optimizing gas & auditing during the development of smart contracts on Solidity! Original Image | (2) Today we also kick off a unique 3-part series in which we will discus...

Pod Startup Time Improvements

In a Kubernetes environment, deploying and managing Java backend applications within pods can introduce challenges related to pod startup time. The time it takes for pods to transition from initialization to full operational status can have significant implications for application performance and us...

Spark Job Optimizations & Databricks

There are several ways a spark job can be optimized. Using the right optimization is crucial to reduce the overall runtime and compute cost. In my project, I was given a task to optimize the spark jobs and reduce the overall run time of long-running Airflow DAGs. In this blog, I am going to discu...

Build Time Optimizations (Xcode)

As an iOS developer, we have encountered this problem frequently whereby, after starting the build, it takes a long time to get compiled and built which in turn tends to distract us from our focus zone and reduces productivity. Courtesy @ios_memes So we drilled down to identify and ta...

Route Optimization: Getting Google Cloud and OSRM set up

American Tire Distributors delivery drivers accumulate more than 80 million miles per year, making nearly 7 million deliveries to customers annually. We’re always looking at ways we can enhance the customer experience throughout the delivery process. From the moment we receive the ti...

Step-by-Step Guide to Bayesian Optimization: A Python-based Approach

 consider a function f that is inaccessible to us. We cannot directly access f or compute its gradients. Our only available information is providing an input x and receiving a noisy estimation (or without any noise) of the true output. Our objective is to op...