Speedata Raises $44M to Challenge Nvidia with Innovative Analytics Processing Unit

Speedata, a chip startup competing with Nvidia, raises a $44M Series B | TechCrunch

Speedata, a Tel Aviv-based startup developing an analytics processing unit (APU) designed to accelerate big data analytic and AI workloads, has raised a $44M Series B funding round, bringing its total capital raised to $114M. The Series B round was led by its existing investors, including Walden Catalyst Ventures, 83North, Koch Disruptive Technologies, Pitango First, and Viola Ventures, as well as strategic investors, including Lip-Bu Tan, CEO of Intel and Managing Partner at Walden Catalyst Ventures, and Eyal Waldman, Co-Founder and former CEO of Mellanox Technologies. The APU architecture focuses on addressing the specific bottlenecks of analytics at the computing level, unlike graphics processing units (GPUs), which were initially designed for graphics and later modified for AI and data-related tasks, according to the startup. "For decades, data analytics have relied on standard processing units, and more recently, companies like Nvidia have invested in pushing GPUs for analytics workloads," Adi Gelvan, CEO of Speedata, said in an interview with TechCrunch. "But these are either general-purpose processors or processors designed for other workloads, not chips built from the ground up for data analytics. Our APU is purpose-built for data processing and a single APU can replace racks of servers, delivering dramatically better performance." Speedata was founded in 2019 by six founders, some of whom were the first researchers to develop Coarse-Grained Reconfigurable Architecture (CGRA) technology. The founders collaborated with ASIC design experts to address a fundamental problem: data analytics were being performed by general-purpose processors. If the workloads grew too complex, they could need to tap into hundreds of servers. The founders believed that they could develop a single dedicated processor to accomplish the task faster using less energy. "We saw this as an opportunity to put our decades of research in silicon into transforming how the industry processes data," Gelvan said. Its APU currently targets Apache Spark workloads, but its roadmap includes supporting every major data analytics platform, according to the company CEO. "We aim at becoming the standard processor for data processing -- just as GPUs became the default for AI training, we want APUs to be the default for data analytics across every database and analytics platform," Gelvan told TechCrunch. The startup says it has a number of large companies testing its APU, though it declined to name them. The official product launch is set for the Databricks' Data & AI Summit in the second week of June. Gelvan said that they will publicly showcase its APU for the first time at the event. Speedata claims a specific case where its APU completed a pharmaceutical workload in 19 minutes, which was significantly faster than the 90 hours it took when using a non-specialized processing unit, resulting in a 280x speed improvement. The startup said it has achieved several milestones since its last fundraising, including finalizing the design and manufacturing of its first APU in late 2024. "We've moved from concept to testing on a field-programmable gate array (FPGA), and now we are proud to say we have working hardware that we are currently launching. We already have a growing pipeline of enterprise customers eagerly waiting for this technology and were ready to scale our go-to-market operations," Gelvan, said.

Data analytics chip startup Speedata closes $44M funding round - SiliconANGLE

Data analytics chip startup Speedata closes $44M funding round Speedata Ltd, the developer of a chip optimized for data analytics such as Apache Spark, has raised $44 million in funding. The startup announced the Series B investment today. It included the participation of Walden Catalyst Ventures, 83North, Koch Disruptive Technologies, Pitango First and Viola Ventures. The investment firms were joined by Intel Corp. Chief Executive Officer Lip-Bu Tan and Mellanox Technologies Ltd co-founder Eyal Waldman. Tel Aviv-based Speedata offers an accelerator card called the C200. It can be attached to servers via a standard PCIe port to speed up data analytics workloads. According to Speedata, the C200 doesn't require significant code or infrastructure changes to use, which makes it relatively simple to deploy. The card is based on a custom chip called Callisto. Speedata says that it performs analytics tasks more efficiently than central processing units or graphics cards. Callisto's performance stems partly from its use of a relatively new chip architecture known as CGRA that Speedata's founders helped develop. Similarly to field programmable gate arrays, or FPGAs, a GCRA chip can be programmed for specific tasks to increase the speed at which it competes those tasks. If users run the same SQL query on two different datasets, the query might carry out two entirely different sets of calculations. The reason is that analytics queries often contain so-called branching logic. This means that the calculations performed by a query vary based on the data it processes. Many common data analysis tasks involve branching logic. Graphics cards sometime struggle to process branching logic efficiently. The reason is that some of a graphics card's threads, or units of computing power, are left unused while it's running queries that contain branching logic. Speedata's Callisto chip doesn't share that limitation, which allows it to use threats' processing capacity more fully. The result is an increase in query performance. Callisto also includes a number of other performance optimizations. When performing data analysis tasks, a graphics card must expend a significant amount of processing power on coordinating its different computing modules. The GCRA architecture on which Callisto is based relegates coordination tasks to the computing modules themselves, which reduces the associated overhead. That makes more processing capacity available for queries. Many analytics applications store their data in a format known as an Apache Parquet. Before a Parquet file can be processed, its contents have to be extracted through a multi-step process. This process involves repeatedly moving the file to and from memory, which takes time. Callisto extracts Parquet files' contents without moving them off-chip to a remote memory device and thereby speeds up processing. Speedata says that its chip is significantly faster than less specialized silicon. In one test detailed by the company today, Callisto ran an unspecified pharmaceutical workload about 280 times faster than a competing processor. Speedata says that the chip also being tested beyond the healthcare sector by organizations in the finance, insurance and advertising technology markets. "Everyone knows that AI inference will transform our lives, but none of that happens without data analytics first," said Speedata CEO Adi Gelvan. The company will use its new funding round to finance go-to-market initiatives.

Chip wars heat up: Israeli startup Speedata raises millions to challenge Nvidia with lightning-fast processor

Speedata, an Israeli chip startup, secured $44 million in Series B funding, bringing its total to $114 million. The company is set to unveil its APU, a processor designed to accelerate data analytics workloads, potentially challenging Nvidia's dominance. Speedata's APU demonstrated a 280x speed improvement over traditional hardware in pharmaceutical testing.The battle for supremacy in AI and big data computing just got more competitive after an Israeli chip startup Speedata raised $44 million in a Series B funding round, bringing its total capital to $114 million as it gears up to unveil a next-generation processor that could shake up the industry and challenge Nvidia's long-standing dominance, as per Benzinga. According to the report, Speedata's innovation is its analytics processing unit (APU), a chip custom-built to accelerate data analytics workloads from the ground up. Unlike GPUs, which were initially designed for graphics and later adapted for AI and data tasks, Speedata's APU is purpose-built solely for data processing, as per Benzinga. ALSO READ: Scale AI's billionaire founder drives a Honda Civic and shops at Shein -- Lucy Guo says it's how you stay rich The funding round was led by existing investors like Walden Catalyst Ventures, 83North, Koch Disruptive Technologies, Pitango First, and Viola Ventures, along with strategic backers including Intel CEO Lip-Bu Tan, who also serves as managing partner at Walden Catalyst, and Eyal Waldman, co-founder of Mellanox Technologies, reported TechCrunch. Speedata CEO Adi Gelvan said, "Our APU is purpose-built for data processing and a single APU can replace racks of servers, delivering dramatically better performance," quoted TechCrunch. He also highlighted that, "We aim at becoming the standard processor for data processing -- just as GPUs became the default for AI training, we want APUs to be the default for data analytics across every database and analytics platform," as quoted in the report. A pharmaceutical test found that the company's APU was able to finish a complex data workload in only 19 minutes, compared to conventional hardware which needs 90 hours, as per Benzinga. This means it is a 280x speed improvement, according to the report. The AI chipmaker startup has planned to showcase its APU publicly for the first time at the Databricks' Data & AI Summit, as per TechCrunch. What does Speedata do? Speedata is an Israeli startup that builds chips specifically for big data and analytics. How much money has Speedata raised so far? The company raised $114 million in total, including $44 million in its latest Series B round, as per Benzinga.

Israeli Chip Startup Speedata Raises $44M To Challenge Nvidia's AI Dominance With 280x Faster Analytics Processor - NVIDIA (NASDAQ:NVDA), Intel (NASDAQ:INTC)

Israeli chip startup Speedata has secured a $44 million Series B round, bringing its total funding to $114 million as it prepares to unveil a next-generation processor that may challenge Nvidia's NVDA dominance in AI and big data computing, TechCrunch reports. The round was led by existing investors, including Walden Catalyst Ventures, 83North, Koch Disruptive Technologies, Pitango First, and Viola Ventures, according to TechCrunch. Strategic backers include Intel INTC CEO Lip-Bu Tan, who also serves as managing partner at Walden Catalyst, and Eyal Waldman, co-founder of Mellanox Technologies. Don't Miss: Maker of the $60,000 foldable home has 3 factory buildings, 600+ houses built, and big plans to solve housing -- this is your last chance to become an investor for $0.80 per share. Wall Street's Missing This AI Surgical Tech -- You Don't Have To. Invest from $350. 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Unlike graphics processing units, which were originally designed for graphics and later adapted for data workloads, Speedata's analytics processing unit was engineered solely for analytics performance. "Our APU is purpose-built for data processing and a single APU can replace racks of servers, delivering dramatically better performance," Speedata CEO Adi Gelvan told TechCrunch. "We aim at becoming the standard processor for data processing -- just as GPUs became the default for AI training, we want APUs to be the default for data analytics across every database and analytics platform," he added. In one pharmaceutical test case, Speedata's APU completed a complex data workload in just 19 minutes, compared to 90 hours using conventional hardware. That represents a 280x speed improvement, highlighting the chip's potential to redefine industry benchmarks, TechCrunch says. Trending: Invest where it hurts -- and help millions heal: Invest in Cytonics and help disrupt a $390B Big Pharma stronghold. The APU currently supports Apache Spark, with a product roadmap that includes integration across major analytics platforms. According to TechCrunch, Speedata aims to position its APU as the industry standard for processing analytics data, similar to how Nvidia's GPUs became essential in AI training. Veteran-Backed Founders Bring Deep Silicon Expertise To Market Speedata was founded in 2019 by six engineers, including early researchers of multi-threaded coarse-grained reconfigurable architecture, a breakthrough in programmable chip technology, TechCrunch reports. The founding team collaborated with application-specific integrated circuit specialists to design the chip from the ground up to solve analytics bottlenecks. Since its last funding round, Speedata has finalized the design and manufacturing of its first APU, moving from prototype simulations to production hardware in late 2024. The company is growing a pipeline of several large enterprise customers, although names have not been disclosed, TechCrunch says. See Also: Maximize saving for your retirement and cut down on taxes: Schedule your free call with a financial advisor to start your financial journey - no cost, no obligation. First Public APU Reveal Scheduled For Databricks Data & AI Summit Speedata plans to showcase its APU publicly for the first time at the Databricks' Data & AI Summit currently underway, according to TechCrunch. The startup is now expanding its go-to-market operations and growing its pipeline of enterprise clients eager to transition to faster and more efficient data processing, TechCrunch says. With $114 million in total funding, Speedata enters the race with both the hardware and investor backing to compete on a global scale. As data workloads continue to grow, Speedata's APU could reshape how businesses process information, potentially giving Nvidia its first serious competitor in data-specific chip architecture. Read Next: Are you rich? Here's what Americans think you need to be considered wealthy. Image: Shutterstock INTCIntel Corp$20.733.35%Stock Score Locked: Edge Members Only Benzinga Rankings give you vital metrics on any stock - anytime. Unlock RankingsEdge RankingsMomentum22.78Growth19.67QualityNot AvailableValue74.73Price TrendShortMediumLongOverviewNVDANVIDIA Corp$142.730.71%Market News and Data brought to you by Benzinga APIs