A few months back, Dell and NVIDIA released a validated design for running NVIDIA Riva on Red Hat OpenShift with Dell PowerFlex. A simple poster—nothing more, nothing less—yet it can unlock much more for your organization. This design shows the power of NVIDIA Riva and Dell PowerFlex to handle audio processing workloads.

What’s more, it will be showcased as part of the poster gallery at NVIDIA GTC this week in San Jose California. If you are at GTC, we strongly encourage you to join us during the Poster Reception from 4:00 to 6:00 PM. If you are unable to join us, you can view the poster online from the GTC website.

For those familiar with ASR, TTS, and NMT applications, you might be curious as to how we can synthesize these concepts into a simple poster. Read on to learn more.

NVIDIA Riva

For those not familiar with NVIDIA Riva, let’s start there.

NVIDIA Riva is an AI software development kit (SDK) for building conversational AI pipelines, enabling organizations to program AI into their speech and audio systems. It can be used as a smart assistant or even a note taker at your next meeting. Super cool, right?

Taking that up a notch, NVIDIA Riva lets you build fully customizable, real-time conversational AI pipelines, which is a fancy way of saying it allows you to process speech in a bunch of different ways including automatic speech recognition (ASR), text-to-speech (TTS), and neural machine translation (NMT) applications:

• Automatic speech recognition (ASR) – this is essentially dictation. Provide AI with a recording and get a transcript—a near perfect note keeper for your next meeting.
• Text-to-speech (TTS) – a computer reads what you type. In the past, this was often in a monotone voice. It’s been around for more than a couple of decades and has evolved rapidly with more fluid voices and emotion.
• Neural machine translation (NMT) – this is the translation of spoken language in near real-time to a different language. It is a fantastic tool for improving communication, which can go a long way in helping organizations extend business.

Each application is powerful in its own right, so think about what’s possible when we bring ASR, TTS, and NMT together, especially with an AI-backed system. Imagine having a technical support system that could triage support calls, sounded like you were talking to an actual support engineer, and could provide that support in multiple languages. In a word: ground-breaking.  

NVIDIA Riva allows organizations to become more efficient in handling speech-based communications. When organizations become more efficient in one area, they can improve in other areas. This is why NVIDIA Riva is part of the NVIDIA AI Enterprise software platform, focusing on streamlining the development and deployment of production AI.

I make it all sound simple, however those creating large language models (LLMs) around multilingual speech and translation software know it’s not so. That’s why NVIDIA developed the Riva SDK.

The operating platform also plays a massive role in what can be done with workloads. Red Hat OpenShift enables AI speech recognition and inference with its robust container orchestration, microservices architecture, and strong security features. This allows workloads to scale to meet the needs of an organization. As the success of a project grows, so too must the project.

Why is Storage Important

You might be wondering how storage fits into all of this. That’s a great question. You’ll need high performance storage for NVIDIA Riva. After all, it’s designed to process and/or generate audio files and being able to do that in near real-time requires a highly performant, enterprise-grade storage system like Dell PowerFlex.

Additionally, AI workloads are becoming mainstream applications in the data center and should be able to run side by side with other mission critical workloads utilizing the same storage. I wrote about this in my Dell PowerFlex – For Business-Critical Workloads and AI blog.

At this point you might be curious how well NVIDIA Riva runs on Dell PowerFlex. That is what a majority of the poster is about.

ASR and TTS Performance

The Dell PowerFlex Solutions Engineering team did extensive testing using the LibriSpeech dev-clean dataset available from Open SLR. With this data set, they performed automatic speech recognition (ASR) testing using NVIDIA Riva. For each test, the stream was increased from 1 to 64, 128, 256, 384, and finally 512, as shown in the following graph.

 Figure 1. NVIDIA Riva ASR Performance

The objective of these tests is to have the lowest latency with the highest throughput. Throughput is measured in RTFX, or the duration of audio transcribed divided by computation time.  During these tests, the GPU utilization was approximately 48% without any PowerFlex storage bottlenecks. These results are comparable to NVIDIA’s own findings in in the NVIDIA Riva User Guide.

The Dell PowerFlex Solutions Engineering team went beyond just looking at how fast NVIDIA Riva could transcribe text, also exploring the speed at which it could convert text to speech (TTS). They validated this as well. Starting with a single stream, for each run the stream is changed to 4, 6, 8, and 10, as shown in the following graph.

Figure 2. NVIDIA Riva TTS Performance

Again, the goal is to have a low average latency with a high throughput. The throughput (RTFX) in this case is the duration of audio generated divided by computation time. As we can see, this results in a RTFX throughput of 391 with a latency of 91ms with ten streams. It is also worth noting that during testing, GPU utilization was approximately 82% with no storage bottlenecks.

This is a lot of data to pack into one poster. Luckily, the Dell PowerFlex Solutions Engineering team created a validated architecture that details how all of these results were achieved and how an organization could replicate them if needed.

Now, to put all this into perspective, with PowerFlex you can achieve great results on both spoken language coming into your organization and converting text to speech. Pair this capability with some other generative AI (genAI) tools, like NVIDIA NeMo, and you can create some ingenious systems for your organization.

For example, if an ASR model is paired with a large language model (LLM) for a help desk, users could ask it questions verbally, and—once it found the answers—it could use TTS to provide them with support. Think of what that could mean for organizations.

It's amazing how a simple poster can hold so much information and so many possibilities. If you’re interested in learning more about the research Dell PowerFlex has done with NVIDIA Riva, visit the Poster Reception at NVIDIA GTC on Monday, March 18^th from 4:00 to 6:00 PM. If you are unable to join us at the poster reception, the poster will be on display throughout NVIDIA GTC. If you are unable to attend GTC, check out the white paper, and reach out to your Dell representative for more information.

Authors: Tony Foster  |  Twitter: @wonder_nerd  |  LinkedIn

                Praphul Krottapalli

                Kailas Goliwadekar