IARPA/Army Seek New ‘Clean Sheet’ Computer Architecture for Data Analysis

By John Russell

December 14, 2021

Earlier this month, the Intelligence Advanced Research Projects Activity (IARPA) and the U.S. Army Combat Capabilities Development Command’s Army Research issued a call for proposals to build a new computer architecture to handle the growing flood of data.

“Clean sheet designs are needed to address today’s era of explosive data growth,” said IARPA AGILE program manager, William Harrod. “Current computers are designed for yesterday’s compute-intensive applications, not today’s data-intensive problems. Our ability to collect data far outpaces our ability to extract meaningful, timely insights, and AGILE seeks to address this problem.”

Proposals for the new program – The Advanced Graphic Intelligence Logical Computing Environment (AGILE) – are due quite soon, on January 18, 2022.

“The word ‘computing’ is not represented in the acronym for the program title,” Harrod said during the proposer’s day program held last December (YouTube link). “That’s because the program is focused on developing new computer architectures for data-intensive appliacations, not compute-intensive applications, [and] besides the ‘C’ would mess up my acroynym.”

The full description of the program (W911NF-S-0001) is online. Excerpted below is the broad problem statement and objective statement from IARPA’s Broad Agency Announcement:

“The key computational problem is that today’s computers were designed to address yesterday’s compute-intensive problems rather than today’s data-intensive problems. Transforming the massive, unstructured, heterogeneous data streams and structures into actionable knowledge could benefit from a reimagining of computing architectures and technologies – one that places primary focus on data movement, storage, and access of irregular and time-varying structures.

“The data of interest is increasingly sparse, unstructured, and heterogeneous, with minimal locality (it is distributed across the computer), poor data re-use, streaming updates flowing into the system, and fine-grain data movement and parallelism. The computations to be performed are determined by the data with multiple applications simultaneously accessing the same data. These are very different conditions than those characteristic of yesterday’s compute-intensive applications.

“The AGILE program seeks innovative, energy-efficient, reliable computer architectures which can address the DoD’s and the IC’s large-scale data-analytic applications, as well as other classes of large problems. This solicitation focuses on developing new system-level intelligent mechanisms for processing, moving, accessing, and storing large, unstructured, time-varying data streams and structures that allow for the scalable and efficient execution of dynamic analytics workflows.

“Acceptable AGILE system designs must emphasize optimizing the fully integrated system, rather than the independent optimization of individual functionalities (e.g., memory or computation). Supporting research and development for these proposed designs do not need to be constrained by existing component interfaces and protocols, legacy architectures, or current practices. It is anticipated that a “clean sheet” approach to designing a computer system for data- intensive applications will be required to meet the AGILE goals.”

IARPA says the proposed computer system designs must consist of four fundamental functions:

  • Communication – the web that permeates the computer structure to provide mechanisms for moving data and executing message-driven remote actions (between and within the nodes in the AGILE System).
  • Memory – mechanisms for accessing and storing the data.
  • Computation – mechanisms for the execution and flow control of tasks.
  • Runtime – infrastructure for executing system and computational tasks.

Below is the description of the AGILE program scope excerpted from the BAA:

“The AGILE program is envisioned as a 36-month effort with two phases. Phase 1 will last 18 months, and Phase 2 will last 18 months. Overall goals for the AGILE program are to create novel computer architectures and designs that overcome the challenges specified below. The AGILE program will result in the delivery of Detailed Designs, whose performance has undergone rigorous and independent Testing and Evaluation (T&E) using the application modeling and simulation environment described in Section A.2.6 Test and Evaluation (T&E).

“The proposed designs must have the following characteristics:

  • Efficient and scalable when executing large-scale data analytics including streaming analytics;
  • Energy efficient, reliable, and able to support scaling from a deskside system to large multi- cabinet configurations. Energy efficiency should be at least equal to today’s computer systems but higher is preferred;
  • Cost effective. The price of computation should be at least equal to today’s computer systems but less expensive is preferred;
  • Secure from an adversary attacks;
  • Realizable in silicon prior to approximately 2030;
  • The IP utilized in the design must be open sourced or licensable by the US Government; and
  • Able to meet the metrics described in Section A.2.3 Program Metrics and Goals.

“We will release four workflows plus their derivative kernels, and three industry standard benchmarks to drive the research and development of the AGILE system designs. Offerors should propose a research project that develops a computer design driven by the four AGILE Workflows, Kernels and Benchmarks.”

Link to IARPA release: https://www.iarpa.gov/newsroom/article/iarpa-and-army-to-engineer-next-generation-of-computers

Link to program description: https://www.arl.army.mil/wp-content/uploads/2021/11/W911NF-22-S-0001-Advanced-Graphic-Intelligence-Logical-Computing-Environment-AGILE.pdf

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion XL — were added to the benchmark suite as MLPerf continues Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire