Whileone Tech Space

DLRM stands for Deep Learning Recommendation Model. It is a neural network architecture developed by Facebook AI (Meta) for large-scale personalized recommendation systems. DLRM is widely used in real-world applications  where personalized recommendations or ranking predictions are needed. DLRM designed for click-through rate (CTR) prediction and ranking task.  Examples: Online Advertising, E-commerce Recommendations, Social Media Feed Ranking, Streaming Services, Online Mark

1. The Software Ecosystem is Now the Core Focus The most significant shift was the overwhelming emphasis on software, tools, and developer experience. Platform Mindset: Keynote speakers, including executives from major players, stressed the need to view RISC-V not just as an ISA (Instruction Set Architecture) but as an ecosystem that requires platform-level thinking. The message was clear: no single company can build the entire software stack alone; continued, sustained commu

The Leap into the Unknown Stepping out of the academic bubble and into the professional world is often painted as a daunting transition. For us, it was less a leap of faith and more an excited dive into the deep end, specifically, into the innovative waters of WhileOne.Our motivation to join was simple yet profound: we sought a place where curiosity was celebrated, challenges were seen as growth opportunities, and real-world impact was a daily pursuit. Little did we know that

Complex computing environments, spanning cloud, HPC, AI, and edge workloads; observability is no longer optional. With multiple layers of hardware and software working together, traditional monitoring alone cannot surface the insights needed for optimizing performance or preventing downtime. At Whileone Techsoft Pvt. Ltd. , we help companies go beyond monitoring by building deep observability frameworks that connect performance benchmarking , system analytics , telemetry , an

Delivering Modernization, Benchmarking & Cost Efficiency Migrating workloads from AMD64 to ARM64 allows organizations to harness the...

Meta’s Llama 4 Scout, released in April 2025, is a 17-billion parameter general-purpose language model that brings powerful reasoning to a broader range of applications—including those running without GPUs. This blog focuses on benchmarking Llama 4 Scout on CPU-only systems, covering: Tokens per second Latency per token Prompt handling efficiency Quantization techniques Architecture-specific optimization for x86, ARM, and RISC-V (RV64) Converting to GGUF format for efficient

JetStream is a JavaScript benchmark suite that evaluates web application performance by measuring the execution latency and throughput of complex workloads. With the release of JetStream 2.2, we at WhileOne Techsoft undertook the task of migrating its harness to a modern Node.js-based setup . Recently while working with a customer who was looking to benchmark their CPU using some js workloads. This post dives into why we did it, how we did it, and what you can expect from th

Regression testing   in CI/CD plays a crucial role in maintaining software quality and reliability. Re-running previously executed tests ensures that new code changes do not break existing functionality. Implementing CI/CD in GitLab Since our repository is used by multiple teams, we have implemented CI/CD at the Git level  using GitLab. Our pipeline follows a structured approach, defined in a .yml file. 1. Test Stage When a merge request is created, the following steps are e

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

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 Performa

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

The Problem statement: Our customer expressed their desire to know if Android (AOSP) was already ported by community to the RiscV platform and if we could provide a detailed summary of the current status of AOSP compilation/build and Qemu emulation progress for RiscV What have we accomplished in Part - I: We launched a Bare Metal instance on AWS Downloaded the AOSP source code Configured and built the binaries for AOSP RiscV What we plan to accomplish in Part - II: Install Cu

The Problem statement: Our customer expressed their desire to know if Android (AOSP) was already ported by community to the RiscV platform and if we could provide a detailed summary of the current status of AOSP compilation/build and Qemu emulation progress for RiscV Introduction to AOSP: Android is an open source operating system for mobile devices and an open source project led by Google. Android Open Source Project (AOSP) repository offers the information and source code

Goal of this project: This project aims to determine RISC-V's readiness for running YOLOX for the latest edge requirements. Target Application: Running YOLOX on RISC-V QEMU involves setting up a RISC-V virtual machine and then configuring the necessary environment to compile and run YOLOX. Please note that this is a complex process, and it's essential to have prior experience with virtualization and RISC-V development. From the RISCV website, this is a blog ( https://riscv.or

For some months, we at  WhileOne Techsoft Pvt. Ltd.  have been helping our customer setup a system to validate the performance of their SoC platform. In this context, we had to bring up an aarch64 Linux based target image to run on their proprietary hardware SoC platform. Part -1   of this series explains how to build an external toolchain with BuildRoot. Part -2   of this series explains how to build a target Linux image using an external toolchain (that we built in   Part -

For some months, we at  WhileOne Techsoft Pvt. Ltd.  have been helping our customer setup a system to validate the performance of their SoC platform. In this context, we had to bring up an aarch64 Linux based target image to run on their proprietary hardware SoC platform. Part -1   of this series explains how to build an External Toolchain with BuildRoot. Part -2 of this series explains how to build a Target Linux image and Rootfs in BuildRoot using the External Toolchain th