Phil Lesh’s legendary venue, Terrapin Crossroads, has become a meeting ground and mecca for jam musicians and fans alike. The Grateful Dead bassist consistently invites old friends and new to join him at his intimate San Rafael venue to join in on the fun. This morning, the venue announced that tomorrow, for a special event dubbed Sunshine Daydream (with a tagline of ‘Let there be songs to Phil the air,’ which is also incredible), none other than fellow Grateful Dead member Bob Weir will join the group for an outdoor performance in the backyard of Terrapin Crossroads. Weir will team up with Lesh, along with Grahame Lesh, Jason Crosby, and Scott Law for the evening performance. Tickets are only $12 and are on-sale now here.[Photo via the Terrapin Crossroads Facebook]
On Monday night, Jack White made his way to Seattle, Washington, for a performance at the WaMu Theater. During the show, White paid homage to one of Seattle’s most beloved exports, Pearl Jam, closing the circle on a series of homages between himself and the ’90s grunge-rock heroes.Last week, during Pearl Jam‘s first of two “Home Shows” at Seattle’s Safeco in Seattle, Eddie Vedder delivered an acoustic rendition of The White Stripes‘ “We’re Going To Be Friends”. The song was dedicated to teachers and the band members’ children, with Vedder’s daughters joining the band on stage along with two of their teachers who wore Seattle Mariners jerseys with the name “VEDDER” emblazoned on the back. When Jack White and his new-look touring band made their way to Seattle, White included a cover of Pearl Jam’s “Daughter”, returning the favor in the band’s hometown.You can listen to an audience audio recording of Jack White’s Pearl Jam cover in Seattle below via YouTube user Vurs Wahflez:Jack White – “Daughter” [Pearl Jam cover][Audio: mfc172]Earlier this summer, Jack White and Pearl Jam shared the stage at Lisbon, Portugal’s NOS Alive Festival. Pearl Jam closed out the day’s festivities following White and his band’s performance. During Pearl Jam’s encore rendition of “Porch”, the band referenced White’s performance with teases of “Seven Nation Army”, foreshadowing what was to come. Finally, to close their set, Pearl Jam welcomed White himself to the stage for a rendition of Neil Young‘s “Rockin’ In The Free World”. Watch the onstage collaboration below:Pearl Jam w/ Jack White – “Rockin’ In The Free World” [Neil Young cover][Video: XTV Podcast]For a full list of Jack White’s upcoming tour dates, head to his website. Pearl Jam is set to close their brief summer run later with a pair of two-night runs in Boston and Chicago. For more information, head here.[H/T Consequence of Sound]
Figure 1: Reference ArchitectureDeep Learning WorkflowAs visualized in figure 2, DL usually consist of two distinct workflows, model development and inference.Figure 2: Common DL Workflows: Model development and inferenceThe workflow steps are defined and detailed below.Ingest Labeled Data – In this step, the labeled data (e.g. images and their labels which indicate whether the image contains a dog, cat, or horse.) are ingested into the Isilon storage system. Data can be ingested via NFS, SMB, and HDFS protocols.Transform – Transformation includes all operations that are applied to the labeled data before they are passed to the DL algorithm. It is sometimes referred to as preprocessing. For images, this often includes file parsing, JPEG decoding, cropping, resizing, rotation, and color adjustments. Transformations can be performed on the entire dataset ahead of time, storing the transformed data on Isilon storage. Many transformations can also be applied in a training pipeline, avoiding the need to store the intermediate data.Train Model – In this phase, the model parameters are learned from the labeled data stored on Isilon. This is done through a training pipeline shown in 3 consisting of the following: This blog was co-authored by Jacci Cenci, Sr. Technical Marketing Engineer, NVIDIAOver the last few years, Dell EMC and NVIDIA have established a strong partnership to help organizations accelerate their AI initiatives. For organizations that prefer to build their own solution, we offer Dell EMC’s ultra-dense PowerEdge C-series, with NVIDIA’s TESLA V100 Tensor Core GPUs, which allows scale-out AI solutions from four up to hundreds of GPUs per cluster. For customers looking to leverage a pre-validated hardware and software stack for their Deep Learning initiatives, we offer Dell EMC Ready Solutions for AI: Deep Learning with NVIDIA, which also feature Dell EMC Isilon All-Flash storage. Our partnership is built on the philosophy of offering flexibility and informed choice across a broad portfolio.To give organizations even more flexibility in how they deploy AI with breakthrough performance for large-scale deep learning Dell EMC and NVIDIA have recently collaborated on a new reference architecture that combines the Dell EMC Isilon All-Flash scale-out NAS storage with NVIDIA DGX-1 servers for AI and deep learning (DL) workloads.To validate the new reference architecture, we ran multiple industry-standard image classification benchmarks using 22 TB datasets to simulate real-world training and inference workloads. This testing was done on systems ranging from one DGX-1 server, all the way to nine DGX-1 servers (72 Tesla V100 GPUs) connected to eight Isilon F800 nodes.This blog post summarizes the DL workflow, the training pipeline, the benchmark methodology, and finally the results of the benchmarks.Key components of the reference architecture shown in figure 1 include:Dell EMC Isilon All-Flash scale-out NAS storage delivers the scale (up to 33 PB), performance (up to 540 GB/s), and concurrency (up to millions of connections) to eliminate the storage I/O bottleneck keeping the most data hungry compute layers fed to accelerate AI workloads at scale.NVIDIA DGX-1 servers which integrate up to eight NVIDIA Tesla V100 Tensor Core GPUs fully interconnected in a hybrid cube-mesh topology. Each DGX-1 server can deliver 1 petaFLOPS of AI performance, and is powered by the DGX software stack which includes NVIDIA-optimized versions of the most popular deep learning frameworks, for maximized training performance. Validate Model – Once the model training phase completes with a satisfactory accuracy, you’ll want to measure the accuracy of it on validation data stored on Isilon – data that the model training process has not seen. This is done by using the trained model to make inferences from the validation data and comparing the result with the label. This is often referred to as inference but keep in mind that this is a distinct step from production inference.Production Inference – The trained and validated model is then often deployed to a system that can perform real-time inference. It will accept as input a single image and output the predicted class (dog, cat, horse). Note that the Isilon storage and DGX-1 server architecture is not intended for and nor was it benchmarked for production inference.Benchmark Methodology SummaryIn order to measure the performance of the solution, various benchmarks from the TensorFlow Benchmarks repository were carefully executed. This suite of benchmarks performs training of an image classification convolutional neural network (CNN) on labeled images. Essentially, the system learns whether an image contains a cat, dog, car, train, etc.The well-known ILSVRC2012 image dataset (often referred to as ImageNet) was used. This dataset contains 1,281,167 training images in 144.8 GB. All images are grouped into 1000 categories or classes. This dataset is commonly used by deep learning researchers for benchmarking and comparison studies.When running the benchmarks on the 148 GB dataset, it was found that the storage I/O throughput gradually decreased and became virtually zero after a few minutes. This indicated that the entire dataset was cached in the Linux buffer cache on each DGX-1 server. Of course, this is not surprising since each DGX-1 server has 512 GB of RAM and this workload did not significantly use RAM for other purposes. As real datasets are often significantly larger than this, we wanted to determine the performance with datasets that are not only larger than the DGX-1 server RAM, but larger than the 2 TB of coherent shared cache available across the 8-node Isilon cluster. To accomplish this, we simply made 150 exact copies of each image archive file, creating a 22.2 TB dataset.Benchmark ResultsFigure 5: Image classification training with original 113 KB imagesThere are a few conclusions that we can make from the benchmarks represented above.Image throughput and therefore storage throughput scale linearly from 8 to 72 GPUs.The maximum throughput that was pulled from Isilon occurred with ResNet50 and 72 GPUs. The total storage throughput was 5907 MB/sec.For all tests shown above, each GPU had 97% utilization or higher. This indicates that the GPU was the bottleneck.The maximum CPU utilization on the DGX-1 server was 46%. This occurred with ResNet50.Large Image TrainingThe benchmarks in the previous section used the original JPEG images from the ImageNet dataset, with an average size of 115 KB. Today it is common to perform DL on larger images. For this section, a new set of image archive files are generated by resizing all images to three times their original height and width. Each image is encoded as a JPEG with a quality of 100 to further increase the number of bytes. Finally, we make 13 copies of each image archive file. This results in a new dataset that is 22.5 TB and has an average image size of 1.3 MB.Because we are using larger images with the best JPEG quality, we want to match it with the most sophisticated model in the TensorFlow Benchmark suite, which is Inception-v4.Note that regardless of the image height and width, all images must be cropped and/or scaled to be exactly 299 by 299 pixels to be used by Inception-v4. Thus, larger images place a larger load on the preprocessing pipeline (storage, network, CPU) but not on the GPU.The benchmark results in Figure 5 were obtained with eight Isilon F800 nodes in the cluster.Figure 6: Image classification training with large 1.3 MB imagesAs before, we have linear scaling from 8 to 72 GPUs. The storage throughput with 72 GPUs was 19,895 MB/sec. GPU utilization was at 98% and CPU utilization was at 84%.ConclusionHere are some of the key findings from our testing of the Isilon and NVIDIA DGX-1 server reference architecture:Achieved compelling performance results across industry standard AI benchmarks from eight through 72 GPUs without degradation to throughput or performance.Linear scalability from 8-72 GPUs delivering up to 19.9 GB/s while keeping the GPUs pegged at >97% utilization.The Isilon F800 system can deliver up to 96% throughput of local memory, bringing it extremely close to the maximum theoretical performance limit an NVIDIA DGX-1 system can achieve.Isilon-based DL solutions deliver the capacity, performance, and high concurrency to eliminate the IO storage bottlenecks for AI. This provides a rock-solid foundation for large scale, enterprise-grade DL solutions with a future proof scale-out architecture that meets your AI needs of today and scales for the future.If you are interested in learning more about this, be sure to see the Dell EMC Isilon and NVIDIA DGX-1 servers for deep learning whitepaper. You’ll find the complete benchmark methodology as well as results for batch inference for model validation. It also contains the complete reference architecture including hardware and software configuration, networking, sizing guidance, performance measurement tools, and some useful scripts. All unit prefixes use the SI standard (base 10) where 1 GB is 1 billion bytes.______________________________________________________________________________________________________________________________________________________About the co-authorJacci CenciTechnical Marketing Engineer, NVIDIAJacci has worked for the past two years at NVIDIA with partners and customers to support accelerated computing and deep learning requirements. Prior to NVIDIA, Jacci spent four years as a data center consultant focused on machine learning, big data analytics, technical computing, and enterprise solutions at Dell EMC. Figure 3: Training pipelinePreprocessing – The preprocessing pipeline uses the DGX-1 server CPUs to read each image from Isilon storage, decode the JPEG, crop and scale the image, and finally transfer the image to the GPU. Multiple steps on multiple images are executed concurrently. JPEG decoding is generally the most CPU-intensive step and can become a bottleneck in certain cases.Forward and Backward Pass – Each image is sent through the model. In the case of image classification, there are several prebuilt structures of neural networks that have been proven to work well. To provide an example, Figure 3 below shows the high-level workflow of the Inception-v3 model which contains nearly 25 million parameters that must be learned. In this diagram, images enter from the left and the probability of each class comes out on the right. The forward pass evaluates the loss function (left to right) and the backward pass calculates the gradient (right to left). Each image contains 150,528 values (224*224*3) and the model performs hundreds of matrix calculations on millions of values. The NVIDIA Tesla GPU performs these matrix calculations quickly and efficiently. Figure 4: Inception v3 model architectureOptimization – All GPUs across all nodes exchange and combine their gradients through the network using the All Reduce algorithm. The communication is accelerated using NCCL and NVLink, allowing the GPUs to communicate through the Ethernet network, bypassing the CPU and PCIe buses. Finally, the model parameters are updated using the gradient descent optimization algorithm.Repeat until the desired accuracy (or another metric) is achieved. This may take hours, days, or even weeks. If the dataset is too large to cache, it will generate a sustained storage load for this duration.
Jessica Marter-Kenyon has joined the Peanut Innovation Lab management team as an advisor on gender-related issues. Dr. Marter-Kenyon, who has lived and worked in Rwanda for four years, recently completed a doctoral degree from the University of California at Santa Barbara in geography. Her research focused on the use of population resettlement as an adaptation to climate change. As a postdoctoral research associate with the innovation lab, Marter-Kenyon holds a joint appointment with the Department of Agricultural Leadership, Education and Communication at the University of Georgia’s College of Agricultural and Environmental Sciences.In addition to her experience in research and teaching, Marter-Kenyon worked from 2006 to 2012 with different groups on cook-stove technology in developing countries.The following Q&A with Marter-Kenyon provides more insight into her expertise.How does cooking dovetail with your interests in climate change?Half the world’s population – mostly in the developing world – relies on the combustion of biomass like wood or charcoal as their primary source of energy for cooking, heating and light. The burning of biomass produces greenhouse gases, like methane and nitrogen dioxide, that are major contributors to anthropogenic climate change.The work I did during this early part of my career involved understanding how improved cookstoves, which burn biomass more efficiently, could reduce the contribution of household cooking to global environmental change. So that was initially how I started getting interested in climate issues.I also became fascinated with the linkages between human beings and the natural environment across scales and places: how a child gathering fuelwood in Uganda, or a woman preparing her family’s daily meal in Guatemala, can become linked to global carbon markets or to policy decisions at the United Nations Framework Convention on Climate Change (UNFCCC).Why is gender an important factor when we consider agriculture in a global context?Agriculture everywhere involves both men and women, but a lot of people don’t realize that the specific character of a person’s participation is often tied to their gender.So, for example, women might be more likely to provide the labor associated with weeding a field or selling food at the market. Women are also typically held responsible for reproductive labor at the level of the household (providing childcare, cooking, cleaning, etc.) which needs to be taken into account when planning interventions.Understanding the gendered dimensions of agriculture at all levels of the value chain is crucial for driving progress towards food security and poverty alleviation. At the same time, as a geographer, I’m sensitive to the place-specific nature of these issues. Since gender is socially constructed, its meaning varies between cultures: an investment that works in one place can produce unhelpful outcomes elsewhere so we have to pay attention to the complex ways in which gender interacts with food systems.What have you learned so far about peanuts and their role in the African diet? I had no idea that aflatoxin was such a big issue in peanut production (as well as in other crops), nor about its impact on health and nutrition. I’ve also been impressed to learn how critical a crop peanut is in places that suffer from aridity and/or frequent drought.Peanuts grow well in those environments and can be transformed into a whole bunch of different food products (sauces, snacks, soups, etc.) so it’s a really valuable source of protein and iron in those contexts.
77SHARESShareShareSharePrintMailGooglePinterestDiggRedditStumbleuponDeliciousBufferTumblr,Dennis Zuehlke Dennis is Compliance Manager for Ascensus. Mr. Zuehlke provides clients with technical support on tax-advantaged accounts (including individual retirement accounts, health savings accounts, simplified employee pension plans, and Coverdell education … Web: www.ascensus.com Details The speeches are over, the national political conventions are history, and the road to the White House is entering the final stretch. It is clear from the candidates’ financial disclosures that both Hillary Clinton and Donald Trump are well set for retirement. What is less clear is how a Clinton or Trump administration would affect the general taxpayer’s retirement.The candidates and their respective party platforms both support the Social Security system and want to strengthen it, but in very different ways.The Democratic Party’s platform calls for protecting and expanding Social Security and fighting every effort to cut, privatize, or weaken it. This would mean going against many reforms that have been proposed previously, such as raising the retirement age, cutting cost-of-living adjustments, and reducing earned benefits. Clinton has proposed raising the cap on income that is subject to the Social Security tax (currently $118,500) and expanding the Social Security tax to investment income.The Republican Party’s platform calls for “preserving and modernizing a system of retirement security” and states that saving Social Security is “our moral obligation to those who have trusted in the government’s word.” However, Republicans oppose tax increases and look to the power of the markets to create wealth and secure the future of the Social Security system. The platform calls for all options to be considered in preserving Social Security and notes that current retirees and those close to retirement can be assured of their benefits. Trump has stated that economic growth is the key to preserving Social Security, and that having a robust economy that is growing will help secure Social Security for the future.The candidates and their party platforms provide little detail on positions related to private retirement plans, such as defined benefit plans, 401(k) plans, and IRAs. The Democratic Party platform calls for enacting legislation to ensure that Americans’ earned pension benefits will not be cut and proposes to pay for it by closing tax loopholes that benefit millionaires and billionaires. The platform also supports the Department of Labor’s (DOL) recently released fiduciary rule, stating that Democrats “will fight against any attempt by Republicans in Congress or on Wall Street to roll back the conflict-of-interest rule.” Hillary Clinton also has publicly stated her support for the DOL’s final fiduciary rule.It is clear from an analysis of the candidates’ tax proposals, however, that retirement plans will be affected, regardless of whether Clinton or Trump is the next president. Both have indicated that they would propose limiting the tax benefits for certain income tax deductions and exclusions (not including charitable contributions), such as deductible IRA contributions and 401(k) plan exclusions from income.Hillary Clinton’s tax proposal would increase taxes on high-income households and implement the “Buffet Rule” that would impose a minimum tax rate of 30 percent of adjusted gross income (AGI) on filers with AGI greater than $1 million.In addition, Clinton would cap the tax value of specified deductions or AGI exclusions to 28 percent. The tax value of the exclusion for employee contributions would be reduced to a maximum of 28 percent for defined contribution retirement plans and IRAs instead of allowing taxpayers to exclude the contributions from the full 33 percent, 35 percent, or 39.6 percent that they would otherwise owe. Taxpayers in the 28 percent and lower brackets would be unaffected.Another Clinton proposal would limit contributions to tax-favored retirement accounts, including defined benefit plans, defined contribution plans, and IRAs, once the total of all tax-favored retirement account balances reaches the level adequate to finance the maximum annuity currently permitted for defined benefit plans. Under the proposal, the account balance limit for an individual age 62 in 2015, would be approximately $3.4 million.Both of these proposals were part of President Obama’s final fiscal year budget proposal, as well as previous Obama administration budget proposals.Donald Trump’s tax proposal would reduce the current seven income tax brackets—which range from 10 percent to 39.6 percent—to just three, and dramatically streamline the process. Trump initially proposed three tax brackets of 10 percent, 20 percent, and 25 percent, but has since modified his proposal, adopting the same tax brackets—12 percent, 25 percent, and 33 percent—that House Republicans have proposed.Like Hillary Clinton’s proposal, Donald Trump’s plan also would limit the tax value of certain itemized deductions and exclusions. Trump’s campaign has not specified how it would limit certain itemized deductions and exclusions, but the expectation is that the limitation would be set at 10 percent. This would reduce the tax value for those itemized deductions and exclusions for taxpayers in all three of Trump’s proposed tax brackets.It is still two months before the presidential election, but it is very clear that regardless of who is elected, tax reform will be on the agenda come next January, and tax-favored retirement savings incentives will be under scrutiny. Stay tuned.
32SHARESShareShareSharePrintMailGooglePinterestDiggRedditStumbleuponDeliciousBufferTumblr How Small Acts Can Equal Big ImpactAuthor and serial entrepreneur G. Shawn Hunter is the founder of Mindscaling. His latest book, Small Acts of Leadership: 12 Intentional Behaviors That Lead to Big Impact, argues that it’s the simple things, when done extraordinarily well, that make a great leader.Shawn and I talked about his book and how it’s not always the most extraordinary, sweeping actions that make the biggest impact.I love this philosophy because all of us can make just a few adjustments and improve our leadership today.Do One Thing At A TimeYou advocate that small, incremental choices can lead to a big impact. In your research for this book, what one small choice have you noticed in the most successful leaders? continue reading »
U.S. President Donald Trump walks down the West Wing colonnade to the Rose Garden to deliver an update on the so-called “Operation Warp Speed” program, the joint Defense Department and HHS initiative that has struck deals with several drugmakers in an effort to help speed up the search for effective treatments for the ongoing coronavirus disease (COVID-19) pandemic, at the White House in Washington, November 13, 2020.Carlos Barria | Reuters – Advertisement – President Donald Trump, with two months left in office, last week asked for options on attacking Iran’s main nuclear site, but ultimately decided against taking the dramatic step, a U.S. official said on Monday.Trump made the request during an Oval Office meeting on Thursday with his top national security aides, including Vice President Mike Pence, Secretary of State Mike Pompeo, new acting Defense Secretary Christopher Miller and General Mark Milley, chairman of the Joint Chiefs of Staff, the official said.Trump, who has refused to concede and is challenging the results of the Nov. 3 presidential election, is to hand over power to Democratic President-elect Joe Biden on Jan. 20.- Advertisement – Trump has spent all four years of his presidency engaging in an aggressive policy against Iran, withdrawing in 2018 from the Iran nuclear deal negotiated by his Democratic predecessor, Barack Obama, and imposing economic sanctions against a wide variety of Iranian targets.Trump’s request for options came a day after a U.N. watchdog report showed Iran had finished moving a first cascade of advanced centrifuges from an above-ground plant at its main uranium enrichment site to an underground one, in a fresh breach of its 2015 nuclear deal with major powers.Alireza Miryousefi, spokesman for Iran’s mission to the United Nations in New York, said Iran’s nuclear program is purely for peaceful purposes and civilian use and Trump’s policies have not changed that. “However, Iran has proven to be capable of using its legitimate military might to prevent or respond to any melancholy adventure from any aggressor,” he added.Iran’s 2.4 tonne stock of low-enriched uranium is now far above the deal’s 202.8 kg limit. It produced 337.5 kg in the quarter, less than the more than 500 kg recorded in the previous two quarters by the International Atomic Energy Agency.In January, Trump ordered a U.S. drone strike that killed Iranian General Qassem Soleimani at Baghdad’s airport. But he has shied away from broader military conflicts and sought to withdraw U.S. troops from global hotspots in keeping with a promise to stop what he calls “endless wars.”A strike on Iran’s main nuclear site at Natanz could flare into a regional conflict and pose a serious foreign policy challenge for Biden.Biden’s transition team, which has not had access to national security intelligence due to the Trump administration’s refusal to begin the transition, declined comment. – Advertisement – The official confirmed the account of the meeting in The New York Times, which reported the advisers persuaded Trump not to go ahead with a strike because of the risk of a broader conflict.“He asked for options. They gave him the scenarios and he ultimately decided not to go forward,” the official said.The White House declined comment.- Advertisement –
All provinces infectedThe southern province of Bushehr reported its first three confirmed cases on Thursday, with COVID-19 now officially infecting all of Iran’s 31 provinces.Namaki asked people not to travel as it is “very dangerous” and said reports show “many cars on the roads are taking the virus with them” to uninfected areas.”If you do not treat the situation with special care we will be struggling with this disease for a long time,” he said.The minister called on Iranians to stay home and said even the special coronavirus committee he chairs will hold its meetings remotely online.Limitations on domestic movements will intensify with more checkpoints across the country.”If we identify anyone at city entrances suspected of infection or infected with the virus we will certainly quarantine them for 14 days,” Namaki added.Photos published by state news IRNA showed checkpoints at Tehran-Qom highway where drivers and passengers were checked for fever.According to the minister, the government is considering incentives for nurses and paramedics who voluntarily transfer to centers and hospitals fighting the virus, and is also considering alternatives to cash in daily transactions. “This virus is highly contagious. It is a serious matter, do not joke about it.”The Islamic republic also reported 591 additional confirmed cases of the COVID-19 illness, bringing the total to 3,513 infected.”Until today, samples have been taken of 23,327 suspected cases, only 3,513 of which have been confirmed,” said ministry spokesman Kianoush Jahanpour.According to Jahanpour, Tehran province is the worst-hit with 1,352 confirmed cases, followed by Qom with 386, Gilan with 333 and Esfahan with 238.The Shiite holy city of Qom, south of Tehran, is the epicenter of Iran’s coronavirus outbreak and where its first deaths were reported on February 19.Authorities have since scrambled to halt its rapid spread.”But there is some good news, of the increasing rate of recovery,” Jahanpour said, noting that 739 of the confirmed cases had made recoveries. Topics : Iran on Thursday reported 15 new deaths from the novel coronavirus, raising the national toll to 107, and said it would keep schools and universities closed until early April.But the number of the dead could be higher, according to a tally reported by state news agency IRNA.Data gathered by the agency from medical universities across Iran as of Wednesday night show at least 126 have died, as it lists the toll in Tehran and Gilan — two of the worst-hit provinces — as “unknown”. Iran has already suspended major cultural and sporting events and reduced working hours across the country, which is one of the worst hit after China.”Schools and universities will be closed until the end” of the current Iranian year, health minister Saeed Namaki said in a televised press conference.The Iranian year ends on March 19 and national holidays then last until early April.”People should not consider this as an opportunity to go travelling,” the minister said. “They should stay home and take our warnings seriously.
22 River Crescent, Broadbeach Waters is on the market for $2.69 million.FROM Caribbean-style pool settings to private rooftops and Monte Carlo-inspired cinema rooms, we’ve picked five Gold Coast homes on the market that will entertain you beyond the Christmas and New Year holiday season.According to Eddie Wardale from Kollosche Prestige Agents, a property should have three key elements to be classed as an “entertainer”. The heated pool and tiled spa is on a private beach.Million dollar views come with matching price tags, and 1/7 Boodera Rd in Palm Beach is no exception. The new home was custom built with the latest technology but it’s all about the “360 degree views, sea breezes, screened roof structure, glass balustrade, engineered long life timber decking, light and power for the night time use,” – a perfect spot to celebrate New Year’s Eve. More from news02:37Purchasers snap up every residence in the $40 million Siarn Palm Beach Northless than 1 hour ago02:37International architect Desmond Brooks selling luxury beach villa20 hours ago22-24 Admiralty Drive, Paradise Waters is ideal for private soirees or kids’ parties.At almost $10 million, 22-24 Admiralty Drive, Paradise Waters has a unique point of difference. Sound-proofed, 7-seat home cinema? Check. Indoor pool? Check. State-of-the-art entertainer’s kitchen? Check. Various living wings? Check. But this grand residential property also features a Poinciana tree shielded by a high wall takes pride of place in the middle of manicured lawn, and is “ideal for large-scale entertaining or a safe children’s play area”.The home was designed for Mr Matsushita — the family behind the Panasonic Electronics empire. The residence features a booth-style dining room. 85 Gibraltar Drive, Isle of Capri has carpet sourced from Monte Carlo in the cinema room.Are you not entertained? You will be if you dim the lights and put on a classic favourite in the supersized cinema room with plush carpet sourced from a Monte Carlo casino at 85 Gibraltar Drive, Isle of Capri.Downstairs, a booth-style dining room complements a customised kitchen, complete with a servery window, built-in coffee machine and butler’s pantry.“You’ll adore the flow from the vast lounge room out to the alfresco terrace, where an undercover area awaits,” the listing reads.The heated pool and tiled spa are set against a private sandy beach and there’s a built-in outdoor kitchen. 1/7 Boodera Rd, Palm Beach is on the market for $1.29 million. TOP HOMES 85 Gibraltar Drive, Isle of Capri — price not available35 Southern Cross Drive Surfers Paradise — $3.9 — $4.2 million22-24 Admiralty Drive Paradise Waters — $9.95 million1/7 Boodera Road, Palm Beach — $1.29 million22 River Crescent Broadbeach Waters — $2.69 million The kitchen is central and overlooks the river and pool setting.“Obviously people want the unique rooms like the media rooms, but the big ones are generous decking and the size of the pool,” Mr Wardale said.Mr Wardale said a good vantage point is also a plus.“When Mum or Dad can be in the kitchen and be able to watch over the pool, that is ideal.”A five-bedroom, three-bathroom family home at Broadbeach Waters meets the brief — 22 River Crescent, on the market for $2.69 million, features a dedicated media room, and the sleek kitchen overlooks the outdoor entertaining area. “You’ve got a spa right next to the pool, an expansive deck, and it all looks over the best part of 180 degree water views which makes it very special,” Mr Wardale said. “It’s definitely up there with the top entertainers on the market on the Gold Coast.” 35 Southern Cross Drive, Surfers Paradise also makes the list. It’s on the market for $3.9 — $4.2 million. It has a “supersized” media room.