GSI Technology's APU achieves GPU-level performance for AI, significantly reducing energy consumption, validated by Cornell University research.
Quiver AI Summary
GSI Technology, Inc. announced a new study from Cornell University validating its Associative Processing Unit (APU) technology, which demonstrates that its Compute-In-Memory (CIM) architecture can achieve GPU-level performance for large-scale AI applications while significantly reducing energy consumption. The research highlights that the Gemini-I APU matches the throughput of NVIDIA’s A6000 GPU on specific workloads and consumes over 98% less energy than traditional GPUs, while outperforming standard CPUs in retrieval tasks. GSI's CEO Lee-Lean Shu noted the potential of CIM to disrupt the AI inference market, especially in energy-sensitive applications. The paper, presented at the Micro ’25 conference, establishes a new analytical framework for CIM devices and emphasizes the APU’s advantages in various sectors including edge AI and defense. The company is also looking forward to future advancements in its technology, including the upcoming Gemini-II APU that promises even greater efficiency and performance.
Potential Positives
- GSI Technology's Associative Processing Unit (APU) has been validated by a Cornell University study, demonstrating GPU-class performance with significantly lower energy consumption.
- The APU achieved over 98% lower energy consumption than traditional GPUs, highlighting its efficiency and sustainability benefits in large-scale AI applications.
- The findings reinforce GSI Technology's position in the growing AI inference market, with the potential to disrupt this $100 billion sector.
- The study introduces a new analytical framework that strengthens the APU’s scalability for developers and system integrators, enhancing its market competitiveness.
Potential Negatives
- The press release heavily relies on the findings from a third-party study, which may raise concerns about the company’s own independent validation of its technology and its reliance on external research for credibility.
- The mention of potential risks and uncertainties may generate skepticism among investors regarding the company's future revenues and gross margins, highlighting vulnerabilities within its business model.
- The disclosure of reliance on a limited number of customers for sales indicates a significant risk factor, as fluctuations in this customer mix could materially affect GSI Technology's financial stability.
FAQ
What is the GSI Technology APU?
The GSI Technology APU is an Associative Processing Unit that enables compute-in-memory technology for AI and high-performance computing.
How does the APU compare to traditional GPUs?
The APU delivers GPU-class performance while consuming over 98% less energy, making it more efficient for AI applications.
What are the key benefits of the Gemini-I APU?
The Gemini-I APU offers fast retrieval task performance, significantly reducing processing time by up to 80% compared to standard CPUs.
Where can I find the Cornell study on the APU?
The study titled “Characterizing and Optimizing Realistic Workloads on a Commercial Compute-in-SRAM Device” is available on the GSI Technology website.
What future advancements are planned for GSI's APU technology?
GSI plans to release the Gemini-II APU, which promises approximately 10x faster throughput and improved energy efficiency for AI workloads.
Disclaimer: This is an AI-generated summary of a press release distributed by GlobeNewswire. The model used to summarize this release may make mistakes. See the full release here.
$GSIT Insider Trading Activity
$GSIT insiders have traded $GSIT stock on the open market 3 times in the past 6 months. Of those trades, 0 have been purchases and 3 have been sales.
Here’s a breakdown of recent trading of $GSIT stock by insiders over the last 6 months:
- AVIDAN AKERIB (VP, Associative Computing) sold 10,000 shares for an estimated $38,947
- JACK A. BRADLEY has made 0 purchases and 2 sales selling 8,000 shares for an estimated $26,620.
To track insider transactions, check out Quiver Quantitative's insider trading dashboard.
$GSIT Hedge Fund Activity
We have seen 30 institutional investors add shares of $GSIT stock to their portfolio, and 13 decrease their positions in their most recent quarter.
Here are some of the largest recent moves:
- UBS GROUP AG removed 201,349 shares (-99.1%) from their portfolio in Q2 2025, for an estimated $676,532
- MARSHALL WACE, LLP added 191,161 shares (+inf%) to their portfolio in Q2 2025, for an estimated $642,300
- ARROWSTREET CAPITAL, LIMITED PARTNERSHIP added 159,249 shares (+inf%) to their portfolio in Q2 2025, for an estimated $535,076
- GOLDMAN SACHS GROUP INC added 140,324 shares (+inf%) to their portfolio in Q2 2025, for an estimated $471,488
- JANE STREET GROUP, LLC added 101,799 shares (+inf%) to their portfolio in Q2 2025, for an estimated $342,044
- SUSQUEHANNA INTERNATIONAL GROUP, LLP added 89,533 shares (+inf%) to their portfolio in Q2 2025, for an estimated $300,830
- ACADIAN ASSET MANAGEMENT LLC added 86,707 shares (+inf%) to their portfolio in Q2 2025, for an estimated $291,335
To track hedge funds' stock portfolios, check out Quiver Quantitative's institutional holdings dashboard.
Full Release
SUNNYVALE, Calif., Oct. 20, 2025 (GLOBE NEWSWIRE) -- GSI Technology, Inc. (Nasdaq: GSIT) , the inventor of the Associative Processing Unit (APU), a paradigm shift in artificial intelligence (AI) and high-performance compute (HPC) processing providing true compute-in-memory technology, announced the publication of a paper led by researchers at Cornell University. Findings confirmed that GSI Technology’s APU CIM (Compute-In-Memory) architectures can match GPU-level performance for large-scale AI applications with a dramatic reduction in energy consumption due to high-density and high-bandwidth memory associated with the CIM architecture.
Key findings include:
- GPU-class performance – The Gemini-I APU delivered comparable throughput to NVIDIA’s A6000 GPU on RAG workloads.
- Massive energy advantage – The APU delivers over 98% lower energy consumption than a GPU over various large corpora datasets, underscoring its efficiency and sustainability.
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Faster and more efficient than CPUs
– The APU’s unique design allows it to perform retrieval tasks several times faster than standard CPUs, shortening total processing time by up to 80%.
“Cornell’s independent validation confirms what we’ve long believed—compute-in-memory has the potential to disrupt the $100 billion AI inference market,” said Lee-Lean Shu, Chairman and Chief Executive Officer of GSI Technology. “The APU delivers GPU-class performance at a fraction of the energy cost, thanks to its highly efficient memory-centric architecture.”
Published on ACM and presented at the Micro ’25 conference, the paper by the Cornell research team titled “Characterizing and Optimizing Realistic Workloads on a Commercial Compute-in-SRAM Device,” represents one of the first comprehensive evaluations of a commercial compute-in-memory device under realistic workloads. The Cornell-led team benchmarked the GSI Gemini-I APU against established CPUs and GPUs, focusing on retrieval-augmented generation (RAG) tasks over datasets ranging from 10GB to 200GB.
The researchers’ findings point to significant opportunities for GSI Technology as customers increasingly require performance-per-watt gains across various industries, including Edge AI for power-constrained robotics, drones, and IoT devices, as well as defense and aerospace applications where the APU can deliver high performance in environments with strict energy and cooling constraints.
Mr. Shu continued, “This tremendous work by Cornell highlights CIM advantages using the Gemini-I silicon. Our recently released second-generation APU silicon, Gemini-II, can deliver roughly 10x faster throughput and even lower latency for memory-intensive AI workloads, while further improving energy efficiency. Looking ahead, Plato represents the next step forward, offering even greater compute capability at lower power for embedded edge applications. The APU’s unique combination of speed, efficiency, and programmability positions us to unlock high-growth opportunities across edge AI, data centers, defense, and other markets where energy efficiency is a critical strategic advantage.”
The Cornell study also introduced a new analytical framework for general-purpose compute-in-memory devices, providing optimization principles that strengthen the APU’s position as a scalable platform for developers and system integrators. A copy of the publication can be found on the GSI website at https://gsitechnology.com/characterizing-and-optimizing-realistic-workloads-on-a-commercial-compute-in-sram-device/ .
ABOUT GSI TECHNOLOGY
Founded in 1995, GSI Technology, Inc. is a leading provider of semiconductor memory solutions. GSI's resources are focused on bringing new products to market that leverage existing core strengths, including radiation-hardened memory products for extreme environments and Gemini-I, the associative processing unit designed to deliver performance advantages for diverse artificial intelligence applications. GSI Technology is headquartered in Sunnyvale, California, and has sales offices in the Americas, Europe, and Asia. For more information, please visit
www.gsitechnology.com
.
About ACM
ACM publishes more than 50 scholarly peer-reviewed journals in dozens of computing and information technology disciplines. Available in print and online, ACM's high-impact, peer-reviewed journals constitute a vast and comprehensive archive of computing innovation, covering emerging and established computing research for both practical and theoretical applications. ACM journal editors are thought leaders in their fields, and ACM's emphasis on rapid publication ensures minimal delay in communicating exciting new ideas and discoveries.
Forward-Looking Statements
The statements contained in this press release that are not purely historical are forward-looking statements within the meaning of Section 21E of the Securities Exchange Act of 1934, as amended, including statements regarding GSI Technology’s expectations, beliefs, intentions, or strategies regarding the future. All forward-looking statements included in this press release are based upon information available to GSI Technology as of the date hereof, and GSI Technology assumes no obligation to update any such forward-looking statements. Forward-looking statements involve a variety of risks and uncertainties, which could cause actual results to differ materially from those projected. These risks include those associated with the normal quarterly and fiscal year-end closing process. Examples of risks that could affect our current expectations regarding future revenues and gross margins include those associated with fluctuations in GSI Technology’s operating results; GSI Technology’s historical dependence on sales to a limited number of customers and fluctuations in the mix of customers and products in any period; global public health crises that reduce economic activity; the rapidly evolving markets for GSI Technology’s products and uncertainty regarding the development of these markets; the need to develop and introduce new products to offset the historical decline in the average unit selling price of GSI Technology’s products; the challenges of rapid growth followed by periods of contraction; intensive competition; the continued availability of government funding opportunities; delays or unanticipated costs that may be encountered in the development of new products based on our in-place associative computing technology and the establishment of new markets and customer and partner relationships for the sale of such products; and delays or unexpected challenges related to the establishment of customer relationships and orders for GSI Technology’s radiation-hardened and tolerant SRAM products. Many of these risks are currently amplified by and will continue to be amplified by, or in the future may be amplified by, economic and geopolitical conditions, such as changing interest rates, worldwide inflationary pressures, policy unpredictability, the imposition of tariffs and other trade barriers, military conflicts and declines in the global economic environment. Further information regarding these and other risks relating to GSI Technology’s business is contained in the Company’s filings with the Securities and Exchange Commission, including those factors discussed under the caption “Risk Factors” in such filings.
Source: GSI Technology, Inc.
Contacts:
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Kim Rogers
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Media Relations
Finn Partners for GSI Technology
Ricca Silverio
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Company
GSI Technology, Inc.
Douglas M. Schirle
Chief Financial Officer
408-331-9802