Whileone Tech Space

1. Introduction High-Performance Computing (HPC) is at the core of solving complex computational problems in scientific research, engineering, and large-scale data analysis. Benchmarking plays a critical role in evaluating and optimizing HPC system performance. The Standard Performance Evaluation Corporation (SPEC) provides widely recognized benchmarking suites tailored for different computing environments, helping researchers, businesses, and hardware vendors assess system c

Introduction Deploying web applications manually can be time-consuming and error-prone. Automating the deployment process ensures consistency, reduces downtime, and improves efficiency. In this blog, we will explore how to automate web application deployment on AWS EC2 using GitHub Actions. By the end of this guide, you will have a fully automated CI/CD pipeline that pushes code from a GitHub repository to an AWS EC2 instance, ensuring smooth and reliable deployments. Seamles

Introduction Managing cloud costs is a growing challenge for software and hardware engineers. As cloud services expand, expenses can quickly spiral out of control without proper oversight. Engineers need a cloud cost management tool like CloudNudge to monitor, optimize, and reduce cloud spending efficiently. In this blog, we will explore why cloud cost management is essential, how specialized tools can help, and best practices for using them effectively. The Importance of Clo

Performance engineering is a vital area in software development that guarantees applications function efficiently and effectively. As modern software systems grow more complex, the need for skilled engineers who understand performance becomes increasingly important. This guide will cover five essential performance engineering skills every software engineer should develop to thrive in their careers. Grasping Performance Requirements To start, software engineers must excel at u

Cloud computing has become the backbone of modern businesses, with AWS, Google Cloud (GCP), Microsoft Azure, and Oracle Cloud Infrastructure (OCI) leading the market. Choosing the right cloud provider depends on various factors like pricing, performance, scalability, security, and real-world use cases. In this blog, we’ll break down these aspects to help you make an informed decision, using detailed tables, graphs, and deep insights. 1. Cloud Provider: Pricing Comparison Pric

In today’s software-driven world, ensuring the seamless performance of applications under varying workloads is a necessity. For performance testing, tools like NeoLoad empower testers to simulate real-world conditions and optimize application behavior. In this blog, we’ll delve into the practical use of NeoLoad for WebFocus performance testing, focusing on scenarios like chart rendering, page loads, data uploads, and resource utilization. Understanding the Scope of Performanc

A debugging tool, GCeasy is used while generating reports of performance engineering.

For the past few months, my team and I at WhileOne Techsoft Pvt. Ltd. have been helping our customer setup a system wherein access to a remote server in the cloud for testing can be granted to users. One of our client’s requirements is to generate SSH keys from the JIRA board. In JIRA use a custom script to generate SSH keys which will help our client for project automation. SSH key pairs are two cryptographically secure keys that can be used to authenticate a client to an SS

Introduction: High-Performance Linpack (HPL) is a widely used benchmark for testing the computational performance of computing systems. In this blog post, we explore an intriguing scenario where we conducted HPL tests on two ARM64 machines. Surprisingly, the Host-2 machine exhibited a 20% lower performance than the Host-1 machine in the HPL test. Intrigued by this result, we embarked on a journey to comprehensively diagnose the underlying cause of this performance discrepancy

In the first part of the blog, we described the problem that we intend to solve, the data gathering, post processing, and generating the final training data. In the 2nd part, we will take a look at the Machine Learning model we used for training and for inference with new data. Correlation between various counters We have captured various counters for various benchmarks. Here is a graph that shows the correlation between each counter with every other counter. ​ K Neighbors Re

This blog is the first part of the series in "Server Performance Prediction using Machine Learning Models" OVERVIEW: In the semiconductor industry, a Silicon Cycle takes nearly a year or more from conception to the silicon being available. As soon as the concept comes in, there is immense pressure on the marketing and sales teams to come up with performance numbers for this new generation of the silicon i.e. processor. There is a need for a way to find out what the score coul

In May 2022, one of our customers asked us to tune Elasticsearch with Esrally for cloud providers. We started with trying multiple combinations of manual runs on all cloud providers. We were collecting scaling runs with 2/4/8/16 cores. In the above data collection, we could not see the proportionate scores. Hence, we decided to experiment with running the Elasticsearch ESRally benchmark throughout the day. As Esrally doesn’t run for a particular duration, we carried out the r

At Whileone we take pride in customer's success. We help customers achieve goals and execute out of the box ideas that are necessary for success. One such project was to get IPCs for cloud applications on different architectures, completely omitting network stack. This would give the RISC-V chip designing customer a good picture whether architecture IPC ( Instructions per Cycle ) is inline with competition like Intel or ARM. To achieve this, we modified cloud applications to

Basic Linear Algebra Subprograms(BLAS) and BLAS Like Interface Software(BLIS) are libraries that can accelerate mathematical operations on current CPU microarchitectures. As a part of the FLAME project, BLIS was introduced to handle the dense linear algebra software stack. The framework was designed to isolate essential kernels of computation that, when optimized, immediately enable optimized implementations of most of its commonly used and computationally intensive operation

One way to scale a Node-based system is to run multiple instances of the server. This approach also works well for Strapi because Strapi doesn't store anything in-memory on the server-side (no sticky sessions). The JWT tokens it issues persist in the database. So, any time we observe a Strapi setup struggling to handle the load of requests on the Node side, we add more instances running the same code. For setups with a predictable workload, pm2 offers a simple way to manage m