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USC's Information Sciences Institute Develops CASPER Compiler on Summit

USC's Information Sciences Institute Develops CASPER Compiler on Summit
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Priceless Astronomy Data Saved After Collapse of Arecibo Telescope

Date Time Priceless Astronomy Data Saved After Collapse of Arecibo Telescope AUSTIN, Texas – When Puerto Rico’s famed Arecibo telescope collapsed in 2020, astronomers lost access to one of the world’s most treasured pieces of equipment – but also, potentially, decades of priceless data holding still undiscovered secrets about the universe. Now, thanks to a data rescue plan led by the Texas Advanced Computing Center at The University of Texas at Austin, Arecibo’s observations will be preserved for generations of future astronomers. Millions of people have seen footage of the collapse in December 2020 of the famed Arecibo radio telescope. The 900-ton spidery-looking instrument platform snapped its gossamer-like suspension cables, which sent it crashing through the radio dish below and into the Puerto Rican countryside, destroying the giant telescope.

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BlueCat Networks: BlueCat taps industry pioneers for IT community's first annual DDI Day celebration

BlueCat Networks: BlueCat taps industry pioneers for IT community's first annual DDI Day celebration TORONTO, April 06, 2021 (GLOBE NEWSWIRE) -- BlueCat, the Adaptive DNS TM company, announced today that it will be hosting the first annual, industry-wide celebration called DDI Day on April 13th. DDI denotes a combination of the critical network services - DNS, DHCP, and IP Address Management - without which digital connectivity is impossible. DDI Day recognizes the heroic efforts of IT professionals who keep these services working, and consequently, our world moving. DDI Day celebrations will feature: A panel discussion by industry pioneers Paul Mockapetris, Ralph Droms, and Russ White. Attendance is free via this

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Intel, Microsoft Aim for Breakthrough in DARPA ...

Intel, Microsoft Aim for Breakthrough in DARPA Encryption Project Together, the vendor giants aim to make "in use" encryption -- also known as "fully homomorphic encryption" -- economical and practical. The widespread encryption of data while stored on disk and communicated through the network — often called "at rest" and "in transit" — are critical security measures to protect business and personal data. Now Intel and Microsoft hope to create a practical and usable implementation of a third measure — "in use" encryption — that could allow encrypted data to be processed without decryption. More formally known as fully homomorphic encryption (FHE), this area of cryptography research has already produced algorithms and systems that can manipulate encrypted data in very specific ways — for, say, averaging or searching. When the data in unencrypted, the result is the same as if the operation had been performed on the plaintext data. Yet FHE is costly, with processing requiring up to a million times more work to perform — a calculation that may take milliseconds to perform will instead take hours, days, or weeks, says Rosario Cammarota, principal engineer at Intel Labs.

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Duality Technologies Awarded $14.5M DARPA Contract to Develop World's Fastest Privacy-Preserving Hardware Accelerator

  Duality Technologies, a leading provider of Privacy-Enhancing Technologies (PETs) based on Homomorphic Encryption (HE), today announced it has been awarded a $14.5M contract from the DPRIVE program. Under the contract with DARPA, Duality will lead a team developing a novel ASIC (Application-specific Integrated Circuit) - code named 'TREBUCHET' - to accelerate computations using Fully Homomorphic Encryption (FHE), with the goal of making FHE cost-effective for even the most challenging high-value applications. FHE is an advanced cryptographic technique, widely considered the 'holy grail of encryption,' which enables multiple users to process and glean insights on encrypted data while the data or models remain encrypted, preserving data privacy throughout the analytics process. This new hardware is crucial in helping data scientists cross the next frontier in FHE: the ability to train some of the most advanced machine learning (ML) models on encrypted data, enabling organizations to leverage greater amounts of diverse sensitive data for training. 

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