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Hi HN,
Pranay and Ankit here. Weâre founders of SigNoz ( https://signoz.io ), an open source observability platform. We are building an open-core alternative to DataDog for companies that are security and privacy conscious, and are concerned about huge bills they need to pay to SaaS observability vendors.
Observability means being able to monitor your application components - from mobile and web front-ends to infrastructure, and being able to ask questions about their states. Things like latency, error rates, RPS, etc. Better observability helps developers find the cause of issues in their deployed software and solve them quickly.
Ankit was leading an engineering team, where we became aware of the importance of observability in a microservices system where each service depended on the health of multiple other services. And we saw that this problem was getting more and more important, esp. in todayâs world of distributed systems.
++ MACHINE LEARNING INTERN, DATA SCIENCE INTERN, SOFTWARE DEVELOPER ++
My interests include computer vision, machine learning and data science. I am doing a double major in Mathematics & Computer Science with expected graduation in Spring 2022. I have shown excellent performance in university courses and have been a student assistant for both Math and Computer Science department. From May 2020 to December 2020, I have been a part of Computer Vision team in Ablera, where I was researching and developing convolutional neural networks for car damage detection. I am looking for a place where I will be able to use my skills in mathematical modelling and an environment where I will be able to grow and learn new things.
Here the findings are largely unchanged from 2018: for the selected
benchmark code, the code generation by our selected compilers has not
changed significantly.
Only the new hardware CPU influences the measurements: the new CPU has
a higher clock frequency than previously, so for an equivalent
mix of instructions we expect and observe a 10-40% raw performance
improvement. Additionally, the Ryzen 7 3950X architecture has a
somewhat more powerful superscalar execution unit than the 1800X, and
is able to detect inter-instruction dependencies across more memory
accesses. This causes more measurements artifacts when the workload is
extremely small, and erases the performance differences between 1 and