{"id":10411,"date":"2013-08-27T23:56:08","date_gmt":"2013-08-27T20:56:08","guid":{"rendered":"http:\/\/hgpu.org\/?p=10411"},"modified":"2013-08-27T23:56:08","modified_gmt":"2013-08-27T20:56:08","slug":"solutions-for-optimizing-the-monte-carlo-option-pricing-methods-implementation-using-the-compute-unified-device-architecture","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=10411","title":{"rendered":"Solutions for Optimizing the Monte Carlo Option Pricing Method&#8217;s Implementation Using the Compute Unified Device Architecture"},"content":{"rendered":"<p>Finance-related problems require more and more computations; therefore, the problem of finding efficient implementations for option pricing models on modern architectures has become an important challenge. Although there are numerous implementations of the Monte Carlo method on central processing units, many of them face limitations arising from the necessary increased computational power. In this paper, we have implemented the Monte Carlo approach to option pricing using the Compute Unified Device Architecture and its optimization solutions.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Finance-related problems require more and more computations; therefore, the problem of finding efficient implementations for option pricing models on modern architectures has become an important challenge. Although there are numerous implementations of the Monte Carlo method on central processing units, many of them face limitations arising from the necessary increased computational power. In this paper, [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[89,576,3],"tags":[14,1804,20,1306,298],"class_list":["post-10411","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-finance","category-paper","tag-cuda","tag-finance","tag-nvidia","tag-nvidia-geforce-gtx-680","tag-optimization"],"views":2495,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/10411","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=10411"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/10411\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=10411"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=10411"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=10411"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}