Blog

31Jul

InAccel Accelerates XGboost and releases the IP core for FPGAs

InAccel has released today as open-source the FPGA IP core for the training of XGboost. The FPGA accelerated solution for the XGBoost algorithm is based on the Exact (Greedy) algorithm for tree creation. It can provide up to 26x speedup compared to a single threaded execution and up to 5x compared to an 8 threaded CPU execution respectively

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18Jul

InAccel releases world’s first universal bitstream repository for FPGAs based on JFrog

InAccel, a company specialized on FPGA accelerators, developed world’s first bitstream repository for FPGAs based on the JFrog artifactory.

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28Jun

InAccel releases open-source Logistic Regression IP core for FPGAs

InAccel has released today as open-source the FPGA IP core for the training of logistic regression algorithms. The accelerated FPGA IP core offers up to 70x speedup compared to a single threaded execution and up to 12x compared to an 8-core general purpose CPU execution respectively.

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26Jun

InAccel releases world's first FPGA orchestrator

InAccel, a start-up company specialized on accelerators for machine learning, has released today the latest version of the Coral FPGA resource manager that allows the software community to instantiate and utilize a cluster of FPGAs with the same easy as invoking typical software functions. InAccel’s Coral FPGA resource manager allows multiple applications to share and utilize a cluster of FPGAs in the same node (server) without worrying about the scheduling, load balancing and the resource management of each FPGA.

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03Jun

FPGAs goes serverless on kubernetes

31Jul InAccel Accelerates XGboost and releases the IP core for FPGAs InAccel has released today as open-source the FPGA IP core for the training of XGboost. The FPGA accelerated solution for the XGBoost algorithm is based on the Exact (Greedy) algorithm for tree creation. It can provide up to 26x speedup compared to a single […]

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13May

How to save over $700k on your next machine learning project

How to save over $700k on your next machine learning project using FPGA-based hardware accelerators and without changing your code at all.

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10Apr

Accelerated Spark ML on top Microsoft SQL Server 2019 Big Data Cluster

Check how you can run 15x faster your Spark ML applications connected to Microsoft SQL server 2019.

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01Apr

FPGA meets Apache Arrow

In this article, we introduce a novel framework that allows the seamless integration of FPGAs under Apache Arrow development platform. The integration of FPGA with Apache Arrow-compatible frameworks allows the acceleration of data science applications without any prior experience on FPGAs.

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20Mar

InAccel releases Coral Resource Manager for seamless deployment of FPGA clusters

InAccel today released the new version of the Coral FPGA resource manager that allow FPGA users to seamlessly deploy and manage FPGA cluster on the cloud or on-premise.

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28Jan

Accelerate ML training on AWS and Reduce the TCO

Check how you can use the new f1 Accelerators on AWS to speedup and reduce the TCO of Machine Learning training

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03Jan

Accelerated Machine Learning training with a push of a button

InAccel, a world-leader in application acceleration, has released today the new Accelerated Machine Learning suite through the Nimbix Cloud infrastructure. The Nimbix Cloud offers both enterprise software users and application developers a platform for accelerated computing for next-generation datacenter applications.

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27Dec

Containerized FPGA Manager for Seamless Application Acceleration and Infrastructure Scalability

InAccel exploits the high computational efficiency of FPGAs to deliver application acceleration services that provides up to 10x faster execution along with 3x cost reduction. Our belief as well as fundamental design focus is that acceleration must be delivered effortless to the user. To this end, InAccel offers seamless infrastructure as well as application integration.

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17Dec

CPU, GPU, FPGA or TPU: Which one to choose for my Machine Learning training?

Currently, cloud providers offer a plethora of choices when it comes to the processing platform that will be used to train your machine learning application. AWS, Alibaba cloud, Azure and Huawei offers several platforms such as general purpose CPUs, compute-optimized CPUs, memory-optimized CPUs, GPUs, FPGAs and Tensor Flow Processing Units.

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26Nov

How to train your ML model 3x faster without changing your code

Training a ML model can take a lot of time especially when you have to process huge amounts of data. Typical general-purpose processors (CPUs) or GPUs are designed to be flexible but are not very efficient on machine learning training. In the domain on embedded systems, that problem was solved many years ago by using specialized chips that are designed for specific applications (i.e. FPGAs). FPGAs are programmable chips that can be configured with specialized architectures. In the FPGAs, instructions that needs to process the data are hard-wired in the chip. Therefore, they can achieve much better performance than CPUs and consume much lower power.

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26Oct

Accelerating Data Science

Emerging cloud applications like machine learning, AI and big data analytics require high performance computing systems that can sustain the increased amount of data processing without consuming excessive power. Towards this end, many cloud operators have started adopting heterogeneous infrastructures deploying hardware accelerators, like FPGAs, to increase the performance of computational intensive tasks. However, most hardware accelerators lack of programming efficiency as they are programmed using not-so widely used languages like OpenCL, VHDL and HLS.

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09Oct

InAccel at XDF 2018

Inaccel presented the new version of the scalable accelerators for Apache Spark on October 2nd at Xilinx's premier event XDF in San Jose. The new version of the ML accelerators for Apache Spark are scalable to a high number of FPGA nodes without and it is fully integrated with Spark. The new version of the accelerators in the cloud allows up to 3x speedup and 2x lower OpEx compared to contemporary processors.

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05Jul

Press Release

Athens, Greece (July 5, 2018) - InAccel Inc. (https://www.inaccel.com/), provider of FPGA accelerators on the cloud, announces today the completion of a $600,000 seed investment round by Marathon Venture Capital (https://marathon.vc/). InAccel will use the investment to accelerate product development and distribution of its flagship products across public cloud vendors.

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