The data and analytics industry has recently experienced enormous changes with equally massive implications.
These shifts all revolve around Google’s new AI chip design and A2 Virtual machines. Cloud and Data Engineers can now scale-out/up their NVIDIA CUDA-enabled machine learning (ML) and high-performance computing (HPC) workloads at a lower cost and higher efficiency.
This blog will examine these industry shifts and then delve into what it means for employers in the data/analytics space.
Diving into Google’s Apollo AI
In March, APOLLO – a framework centered around optimizing AI accelerator chip designs – was announced by Google Research Scientists.
Through its algorithms, APOLLO helps reduce delays with data interpretation by selecting chip parameters.
Compared to designs with more baseline algorithms, those using APOLLO experienced a 24.6% speedup.
APOLLO searches for memory size, I/O bandwidth, processor units, and other hardware limitations. These all offer peak inference performance for specific deep-learning models.
The evolutionary algorithms and transfer learning involved with APOLLO explore the parameter space with peak efficiency. Therefore, it’s possible to produce designs over a significantly reduced time and at a much lower cost.
Furthermore, customized accelerator hardware improves the deep-learning model’s performance.
This accelerator is based on a 2D array of processing elements (PEs) built with multiple single instruction multiple data (SIMD) cores. By choosing values for numerous parameters (e.g., size of the PE array), it’s possible to customize the basic pattern.
Across the design space, there are about 500M parameter combinations. And there’s a need for software simulation for any proposed accelerator designs. So, performance evaluation on a deep-learning model requires lots of time spent working on computers.
Exploring Google’s A2 Virtual Machines
Google’s recent announcement of A2 Virtual Machine’s (VM) general availability has offered a crucial advantage to users:
Customers benefit from lower costs and higher efficiency when running NVIDIA CUDA-enabled machine learning and high-performance computing scale-out and scale-up workloads.
More specifically, the A2 VMs allow customers to choose up to 16 NVIDIA A100 GPUs in a single VM. Even better, they’re choosing from a smaller GPU configuration, which brings more choice and flexibility to scale workloads.
Also, these configurations only require one VM. Beyond that, configuring multiple VMs for a single-node ML training isn’t necessary.
What Do These Changes Mean for the Industry?
These industry shifts are significant, to say the least. And the changes are mostly positive.
All the same, these massive technological developments will be a challenge for data and analytics employers.
Such cutting-edge disruptions are challenging to keep up with. Meaning employers need to be on the lookout for talent with their fingers on the pulse.
Unfortunately, being on top of these trends is a rare find. Even the most talented professionals can get stuck in their ways and are most comfortable and competent in what’s familiar. As such, leadership across data and analytics organizations will be on the hunt for diamonds in the rough.
Since employers are already faced with other responsibilities (such as staying on top of these trends), they don’t always have time to find these rare industry talents. After all, finding the cream of the crops doesn’t happen at the press of a few buttons.
With that said, given how fast technologies are changing, you can’t afford to recruit people who aren’t on top of their trends. So, where can data and analytics employers turn to find high-level talent?
Partnering Up With Specialized Data and Analytics Recruiters.
Instead of spreading yourself too thin as an employer by scouring the ends of the earth for talent, partnering with a specialized recruiter provides a much more efficient hiring solution.
For instance, Synergy System gives data and analytics companies direct access to industry talent who already have expertise in using the tools discussed in this blog.
Contact Synergy Systems today for access to our diverse, top-performing pool of data and analytics talent.