GSI Technology, Inc. Reports Fourth Quarter and Fiscal Year 2020 Results

About this update from Gsi Technology, Inc.

[{"type":"text","content":"SUNNYVALE, Calif., May 07, 2020 (GLOBE NEWSWIRE) -- GSI Technology, Inc. (NASDAQ: GSIT) today reported financial results for its fourth fiscal quarter and fiscal year ended March 31, 2020.\n Fourth Quarter and Fiscal Year 2020 Summary Financial Results Table (in thousands, except per share amounts) Three Months EndedTwelve Months Ended Mar. 31,2020Dec. 31,2019Mar. 31,2019Mar. 31,2020Mar. 31,2019Net revenues$8,535 $10,049 $12,686 $43,343 $51,486 Gross margin (%) 52.5% 60.2% 61.3% 58.5% 61.4%Operating expenses$8,390 $10,792 $8,135 $36,145 $31,810 Operating loss$(3,907)$(4,743)$(365)$(10,802)$(182)Net income (loss)$(3,824)$(4,620)$(102)$(10,337)$163 Net income (loss) per share, diluted$(0.16)$(0.20)$0.00 $(0.45)$0.01 Lee-Lean Shu, Chairman and Chief Executive Officer, commented, “GSI Technology is in a strong financial position. As of March 31, 2020, we had cash, cash equivalents, and short-term and long-term investments of $70.7 million, with no debt. We have a team in-place with tremendous depth and breadth of experience and knowledge, and our legacy business provides an ongoing source of funding for our development of new product lines. The COVID-19 global pandemic has created unique circumstances for all our stakeholders, and we have instituted many preventative measures and are regularly evaluating those measures and others as we continue to better understand our current and future operating environment. Except for our employees located in Taiwan, the majority of our employees are working from home around the world, and productivity remains high. I am grateful for our employees' commitment to delivering continued excellence in product, service, and support.” Mr. Shu continued, “Real-time search of large databases is an increasingly critical function transforming business, scientific and governmental processes. The volume and variety of data, as well as the high velocity required to search enormous datasets in real-time, uses lots of expensive GPUs and CPUs to deliver performance at scale. In early April 2020, we published benchmark results for Gemini-I™ in a billion-scale similarity search on a server containing four Gemini™ APU boards running at a rate of 400 MHz. The results showed that Gemini™ performs extremely fast, accurate searches on large datasets with a smaller footprint and lower power consumption for a much lower t...

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