Aashish Parikh Email & Phone Number

Palo Alto, Ca, Us

San Jose, California, United States

Contextual text summarization and exposition

San Jose, California, United States

I mentor early-stage startup founders (company sizes < 10 employees) as they find customer traction. If we have worked together before and you think I can help, please reach out.Focus areaso Rearchitecting software and backend systems for scaleo Feature experimentation for efficacy and performance

San Jose, California, United States

COVID-19, foundation setup, finance & investments

San Jose, California, United States

At Sigmux, we set out to solve the problem of poor quality, expensive streaming of rich media to mobile devices. We built SynX, an application-aware network cache, to dramatically improve media goodput. Our customers included media/social media companies.Product highlightso SynX initiated in-app caches and discovered peers via proximity, multicast & the Sigmux cloud brokero Content selection personalized via prediction algorithms or app policieso Caches eagerly populated with offline content via peer-to-peer transport via local, unmetered networkso Support for HLS, MPEG4 and raw media modes, special pathways for cached & transparent ad-deliveryo Built-in safeguards: dynamic network calibration, self-throttling & obfuscation for privacy

San Jose, California, United States

Signet provided a low-code environment to build sophisticated backend services. A workflow engine simplified dependency management and deployed services to cloud endpoints.

Mountain View, California, United States

ZeroStack was a venture-funded private cloud company. It combined scale-out, on-premises, secure appliances with a cloud-based self-service management portal to offer the best of private & public clouds. As the founding engineer (employee #1), I worked on almost every part of the product and the company and built large pieces of our underlying infrastructure.Key contributionso Helped build early engineering, product & sales teams to get the company off the groundo Led the early customer interface team, setting up the alpha & beta validation processo Presented ZeroStack’s product at various technical and industry venueso As technical lead, built large parts of the underlying technical infrastructureMemorable technical projectso Integrated hybrid cloud management system - no VMware & AWS VMs left behindo Service-managing sidecars and private-public cloud pipeline for data & control operationso Stats telemetry & events management, OpenStack API integrationo Hyperconverged appliance deployment and private cloud platform

Palo Alto, California, United States

The VMware XLR8+ incubator program was funded by the CEO and run out of the office of the CTO to tackle hard computer science problems that contributed towards VMware’s strategic roadmap.Summaryo Approved as one of 6 company-wide XLR8+ projects in a competitive pitch competitiono Resource management solution for and across private & hybrid cloudso Built and led a new team to develop a composite resource/budget scheduler

Palo Alto, California, United States

DRS matches Virtual Machines (VMs) resource needs by with resource capacities of physical machines. It provides online datacenter intelligence via a recommendation engine that provides algorithmic solutions to load-balancing and other optimization problems in constrained systems.Selected projects - compute & storageo Proactive DRS: Predict resource needs preemptively (cheap, effective) instead of reactively (expensive)o What-if DRS: Model hypothetical scenarios and run experimental algorithmso Distributed Power Management: consolidate idle workloads on fewer host to save powero Storage DRS (disk capacity & I/IO balancing), Storage I/O controlo Key contributor to the core DRS placement, load-balancing and constraint-handling algorithms

Palo Alto, California, United States

The VMM team is the “engine room” of VMware – it provides main system abstractions including virtual CPUs and virtual Memory used to build and realize VMs.Key projectso Deterministic replay and record/replay-based VM fault tolerance: instruction-level determinismo Speculative VM execution: achieving speedup via reordering workloads on multiple CPUso Microarchitecture characterization and verifying hypervisor emulation of architectural invariantso Memory management and interrupt handling in VM contextso Transparent paravirtualization, extending the Linux kernel with the Virtual Machine Interface (VMI)